An I/O controller for virtual pinball machines: accelerometer nudge sensing, analog plunger input, button input encoding, LedWiz compatible output controls, and more.

Dependencies:   mbed FastIO FastPWM USBDevice

Fork of Pinscape_Controller by Mike R

/media/uploads/mjr/pinscape_no_background_small_L7Miwr6.jpg

This is Version 2 of the Pinscape Controller, an I/O controller for virtual pinball machines. (You can find the old version 1 software here.) Pinscape is software for the KL25Z that turns the board into a full-featured I/O controller for virtual pinball, with support for accelerometer-based nudging, a real plunger, button inputs, and feedback device control.

In case you haven't heard of the concept before, a "virtual pinball machine" is basically a video pinball simulator that's built into a real pinball machine body. A TV monitor goes in place of the pinball playfield, and a second TV goes in the backbox to serve as the "backglass" display. A third smaller monitor can serve as the "DMD" (the Dot Matrix Display used for scoring on newer machines), or you can even install a real pinball plasma DMD. A computer is hidden inside the cabinet, running pinball emulation software that displays a life-sized playfield on the main TV. The cabinet has all of the usual buttons, too, so it not only looks like the real thing, but plays like it too. That's a picture of my own machine to the right. On the outside, it's built exactly like a real arcade pinball machine, with the same overall dimensions and all of the standard pinball cabinet hardware.

A few small companies build and sell complete, finished virtual pinball machines, but I think it's more fun as a DIY project. If you have some basic wood-working skills and know your way around PCs, you can build one from scratch. The computer part is just an ordinary Windows PC, and all of the pinball emulation can be built out of free, open-source software. In that spirit, the Pinscape Controller is an open-source software/hardware project that offers a no-compromises, all-in-one control center for all of the unique input/output needs of a virtual pinball cabinet. If you've been thinking about building one of these, but you're not sure how to connect a plunger, flipper buttons, lights, nudge sensor, and whatever else you can think of, this project might be just what you're looking for.

You can find much more information about DIY Pin Cab building in general in the Virtual Cabinet Forum on vpforums.org. Also visit my Pinscape Resources page for more about this project and other virtual pinball projects I'm working on.

Downloads

  • Pinscape Release Builds: This page has download links for all of the Pinscape software. To get started, install and run the Pinscape Config Tool on your Windows computer. It will lead you through the steps for installing the Pinscape firmware on the KL25Z.
  • Config Tool Source Code. The complete C# source code for the config tool. You don't need this to run the tool, but it's available if you want to customize anything or see how it works inside.

Documentation

The new Version 2 Build Guide is now complete! This new version aims to be a complete guide to building a virtual pinball machine, including not only the Pinscape elements but all of the basics, from sourcing parts to building all of the hardware.

You can also refer to the original Hardware Build Guide (PDF), but that's out of date now, since it refers to the old version 1 software, which was rather different (especially when it comes to configuration).

System Requirements

The new config tool requires a fairly up-to-date Microsoft .NET installation. If you use Windows Update to keep your system current, you should be fine. A modern version of Internet Explorer (IE) is required, even if you don't use it as your main browser, because the config tool uses some system components that Microsoft packages into the IE install set. I test with IE11, so that's known to work. IE8 doesn't work. IE9 and 10 are unknown at this point.

The Windows requirements are only for the config tool. The firmware doesn't care about anything on the Windows side, so if you can make do without the config tool, you can use almost any Windows setup.

Main Features

Plunger: The Pinscape Controller started out as a "mechanical plunger" controller: a device for attaching a real pinball plunger to the video game software so that you could launch the ball the natural way. This is still, of course, a central feature of the project. The software supports several types of sensors: a high-resolution optical sensor (which works by essentially taking pictures of the plunger as it moves); a slide potentionmeter (which determines the position via the changing electrical resistance in the pot); a quadrature sensor (which counts bars printed on a special guide rail that it moves along); and an IR distance sensor (which determines the position by sending pulses of light at the plunger and measuring the round-trip travel time). The Build Guide explains how to set up each type of sensor.

Nudging: The KL25Z (the little microcontroller that the software runs on) has a built-in accelerometer. The Pinscape software uses it to sense when you nudge the cabinet, and feeds the acceleration data to the pinball software on the PC. This turns physical nudges into virtual English on the ball. The accelerometer is quite sensitive and accurate, so we can measure the difference between little bumps and hard shoves, and everything in between. The result is natural and immersive.

Buttons: You can wire real pinball buttons to the KL25Z, and the software will translate the buttons into PC input. You have the option to map each button to a keyboard key or joystick button. You can wire up your flipper buttons, Magna Save buttons, Start button, coin slots, operator buttons, and whatever else you need.

Feedback devices: You can also attach "feedback devices" to the KL25Z. Feedback devices are things that create tactile, sound, and lighting effects in sync with the game action. The most popular PC pinball emulators know how to address a wide variety of these devices, and know how to match them to on-screen action in each virtual table. You just need an I/O controller that translates commands from the PC into electrical signals that turn the devices on and off. The Pinscape Controller can do that for you.

Expansion Boards

There are two main ways to run the Pinscape Controller: standalone, or using the "expansion boards".

In the basic standalone setup, you just need the KL25Z, plus whatever buttons, sensors, and feedback devices you want to attach to it. This mode lets you take advantage of everything the software can do, but for some features, you'll have to build some ad hoc external circuitry to interface external devices with the KL25Z. The Build Guide has detailed plans for exactly what you need to build.

The other option is the Pinscape Expansion Boards. The expansion boards are a companion project, which is also totally free and open-source, that provides Printed Circuit Board (PCB) layouts that are designed specifically to work with the Pinscape software. The PCB designs are in the widely used EAGLE format, which many PCB manufacturers can turn directly into physical boards for you. The expansion boards organize all of the external connections more neatly than on the standalone KL25Z, and they add all of the interface circuitry needed for all of the advanced software functions. The big thing they bring to the table is lots of high-power outputs. The boards provide a modular system that lets you add boards to add more outputs. If you opt for the basic core setup, you'll have enough outputs for all of the toys in a really well-equipped cabinet. If your ambitions go beyond merely well-equipped and run to the ridiculously extravagant, just add an extra board or two. The modular design also means that you can add to the system over time.

Expansion Board project page

Update notes

If you have a Pinscape V1 setup already installed, you should be able to switch to the new version pretty seamlessly. There are just a couple of things to be aware of.

First, the "configuration" procedure is completely different in the new version. Way better and way easier, but it's not what you're used to from V1. In V1, you had to edit the project source code and compile your own custom version of the program. No more! With V2, you simply install the standard, pre-compiled .bin file, and select options using the Pinscape Config Tool on Windows.

Second, if you're using the TSL1410R optical sensor for your plunger, there's a chance you'll need to boost your light source's brightness a little bit. The "shutter speed" is faster in this version, which means that it doesn't spend as much time collecting light per frame as before. The software actually does "auto exposure" adaptation on every frame, so the increased shutter speed really shouldn't bother it, but it does require a certain minimum level of contrast, which requires a certain minimal level of lighting. Check the plunger viewer in the setup tool if you have any problems; if the image looks totally dark, try increasing the light level to see if that helps.

New Features

V2 has numerous new features. Here are some of the highlights...

Dynamic configuration: as explained above, configuration is now handled through the Config Tool on Windows. It's no longer necessary to edit the source code or compile your own modified binary.

Improved plunger sensing: the software now reads the TSL1410R optical sensor about 15x faster than it did before. This allows reading the sensor at full resolution (400dpi), about 400 times per second. The faster frame rate makes a big difference in how accurately we can read the plunger position during the fast motion of a release, which allows for more precise position sensing and faster response. The differences aren't dramatic, since the sensing was already pretty good even with the slower V1 scan rate, but you might notice a little better precision in tricky skill shots.

Keyboard keys: button inputs can now be mapped to keyboard keys. The joystick button option is still available as well, of course. Keyboard keys have the advantage of being closer to universal for PC pinball software: some pinball software can be set up to take joystick input, but nearly all PC pinball emulators can take keyboard input, and nearly all of them use the same key mappings.

Local shift button: one physical button can be designed as the local shift button. This works like a Shift button on a keyboard, but with cabinet buttons. It allows each physical button on the cabinet to have two PC keys assigned, one normal and one shifted. Hold down the local shift button, then press another key, and the other key's shifted key mapping is sent to the PC. The shift button can have a regular key mapping of its own as well, so it can do double duty. The shift feature lets you access more functions without cluttering your cabinet with extra buttons. It's especially nice for less frequently used functions like adjusting the volume or activating night mode.

Night mode: the output controller has a new "night mode" option, which lets you turn off all of your noisy devices with a single button, switch, or PC command. You can designate individual ports as noisy or not. Night mode only disables the noisemakers, so you still get the benefit of your flashers, button lights, and other quiet devices. This lets you play late into the night without disturbing your housemates or neighbors.

Gamma correction: you can designate individual output ports for gamma correction. This adjusts the intensity level of an output to make it match the way the human eye perceives brightness, so that fades and color mixes look more natural in lighting devices. You can apply this to individual ports, so that it only affects ports that actually have lights of some kind attached.

IR Remote Control: the controller software can transmit and/or receive IR remote control commands if you attach appropriate parts (an IR LED to send, an IR sensor chip to receive). This can be used to turn on your TV(s) when the system powers on, if they don't turn on automatically, and for any other functions you can think of requiring IR send/receive capabilities. You can assign IR commands to cabinet buttons, so that pressing a button on your cabinet sends a remote control command from the attached IR LED, and you can have the controller generate virtual key presses on your PC in response to received IR commands. If you have the IR sensor attached, the system can use it to learn commands from your existing remotes.

Yet more USB fixes: I've been gradually finding and fixing USB bugs in the mbed library for months now. This version has all of the fixes of the last couple of releases, of course, plus some new ones. It also has a new "last resort" feature, since there always seems to be "just one more" USB bug. The last resort is that you can tell the device to automatically reboot itself if it loses the USB connection and can't restore it within a given time limit.

More Downloads

  • Custom VP builds: I created modified versions of Visual Pinball 9.9 and Physmod5 that you might want to use in combination with this controller. The modified versions have special handling for plunger calibration specific to the Pinscape Controller, as well as some enhancements to the nudge physics. If you're not using the plunger, you might still want it for the nudge improvements. The modified version also works with any other input controller, so you can get the enhanced nudging effects even if you're using a different plunger/nudge kit. The big change in the modified versions is a "filter" for accelerometer input that's designed to make the response to cabinet nudges more realistic. It also makes the response more subdued than in the standard VP, so it's not to everyone's taste. The downloads include both the updated executables and the source code changes, in case you want to merge the changes into your own custom version(s).

    Note! These features are now standard in the official VP releases, so you don't need my custom builds if you're using 9.9.1 or later and/or VP 10. I don't think there's any reason to use my versions instead of the latest official ones, and in fact I'd encourage you to use the official releases since they're more up to date, but I'm leaving my builds available just in case. In the official versions, look for the checkbox "Enable Nudge Filter" in the Keys preferences dialog. My custom versions don't include that checkbox; they just enable the filter unconditionally.
  • Output circuit shopping list: This is a saved shopping cart at mouser.com with the parts needed to build one copy of the high-power output circuit for the LedWiz emulator feature, for use with the standalone KL25Z (that is, without the expansion boards). The quantities in the cart are for one output channel, so if you want N outputs, simply multiply the quantities by the N, with one exception: you only need one ULN2803 transistor array chip for each eight output circuits. If you're using the expansion boards, you won't need any of this, since the boards provide their own high-power outputs.
  • Cary Owens' optical sensor housing: A 3D-printable design for a housing/mounting bracket for the optical plunger sensor, designed by Cary Owens. This makes it easy to mount the sensor.
  • Lemming77's potentiometer mounting bracket and shooter rod connecter: Sketchup designs for 3D-printable parts for mounting a slide potentiometer as the plunger sensor. These were designed for a particular slide potentiometer that used to be available from an Aliexpress.com seller but is no longer listed. You can probably use this design as a starting point for other similar devices; just check the dimensions before committing the design to plastic.

Copyright and License

The Pinscape firmware is copyright 2014, 2021 by Michael J Roberts. It's released under an MIT open-source license. See License.

Warning to VirtuaPin Kit Owners

This software isn't designed as a replacement for the VirtuaPin plunger kit's firmware. If you bought the VirtuaPin kit, I recommend that you don't install this software. The VirtuaPin kit uses the same KL25Z microcontroller that Pinscape uses, but the rest of its hardware is different and incompatible. In particular, the Pinscape firmware doesn't include support for the IR proximity sensor used in the VirtuaPin plunger kit, so you won't be able to use your plunger device with the Pinscape firmware. In addition, the VirtuaPin setup uses a different set of GPIO pins for the button inputs from the Pinscape defaults, so if you do install the Pinscape firmware, you'll have to go into the Config Tool and reassign all of the buttons to match the VirtuaPin wiring.

Plunger/edgeSensor.h

Committer:
mjr
Date:
12 months ago
Revision:
109:310ac82cbbee
Parent:
104:6e06e0f4b476

File content as of revision 109:310ac82cbbee:

// Edge position sensor - 2D optical
//
// This class implements our plunger sensor interface using edge
// detection on a 2D optical sensor.  With this setup, a 2D optical
// sensor is placed close to the plunger, parallel to the rod, with a 
// light source opposite the plunger.  This makes the plunger cast a
// shadow on the sensor.  We figure the plunger position by detecting
// where the shadow is, by finding the edge between the bright and
// dark regions in the image.
//
// This class is designed to work with any type of 2D optical sensor.
// We have subclasses for the TSL1410R and TSL1412S sensors, but other
// similar sensors could be supported as well by adding interfaces for
// the physical electronics.  For the edge detection, we just need an 
// array of pixel readings.

#ifndef _EDGESENSOR_H_
#define _EDGESENSOR_H_

#include "plunger.h"

// Scan method - select a method listed below.  Method 2 (find the point
// with maximum brightness slop) seems to work the best so far.
#define SCAN_METHOD 2
//
//
//  0 = One-way scan.  This is the original algorithim from the v1 software, 
//      with some slight improvements.  We start at the brighter end of the
//      sensor and scan until we find a pixel darker than a threshold level 
//      (halfway between the respective brightness levels at the bright and 
//      dark ends of the sensor).  The original v1 algorithm simply stopped
//      there.  This version is slightly improved: it scans for a few more 
//      pixels to make sure that the majority of the adjacent pixels are 
//      also in shadow, to help reject false edges from sensor noise or 
//      optical shadows that make one pixel read darker than it should.
//
//  1 = Meet in the middle.  We start two scans concurrently, one from 
//      the dark end of the sensor and one from the bright end.  For
//      the scan from the dark end, we stop when we reach a pixel that's
//      brighter than the average dark level by 2/3 of the gap between 
//      the dark and bright levels.  For the scan from the bright end,
//      we stop when we reach a pixel that's darker by 2/3 of the gap.
//      Each time we stop, we look to see if the other scan has reached
//      the same place.  If so, the two scans converged on a common
//      point, which we take to be the edge between the dark and bright
//      sections.  If the two scans haven't converged yet, we switch to
//      the other scan and continue it.  We repeat this process until
//      the two converge.  The benefit of this approach vs the older
//      one-way scan is that it's much more tolerant of noise, and the
//      degree of noise tolerance is dictated by how noisy the signal
//      actually is.  The dynamic degree of tolerance is good because
//      higher noise tolerance tends to result in reduced resolution.
//
//  2 = Maximum dL/ds (highest first derivative of luminance change per
//      distance, or put another way, the steepest brightness slope).
//      This scans the whole image and looks for the position with the 
//      highest dL/ds value.  We average over a window of several pixels, 
//      to smooth out pixel noise; this should avoid treating a single 
//      spiky pixel as having a steep slope adjacent to it.  The advantage
//      in this approach is that it looks for the strongest edge after
//      considering all edges across the whole image, which should make 
//      it less likely to be fooled by isolated noise that creates a 
//      single false edge.  Algorithms 1 and 2 have basically fixed 
//      thresholds for what constitutes an edge, but this approach is 
//      more dynamic in that it evaluates each edge-like region and picks 
//      the best one.  The width of the edge is still fixed, since that's 
//      determined by the pixel window.  But that should be okay since we 
//      only deal with one type of image.  It should be possible to adjust 
//      the light source and sensor position to always yield an image with 
//      a narrow enough edge region.
//
//      The max dL/ds method is the most compute-intensive method, because
//      of the pixel window averaging.  An assembly language implemementation
//      seems to be needed to make it fast enough on the KL25Z.  This method
//      has a fixed run time because it always does exactly one pass over
//      the whole pixel array.
//
//  3 = Total bright pixel count.  This simply adds up the total number
//      of pixels above a threshold brightness, without worrying about 
//      whether they're contiguous with other pixels on the same side
//      of the edge.  Since we know there's always exactly one edge,
//      all of the dark pixels should in principle be on one side, and
//      all of the light pixels should be on the other side.  There
//      might be some noise that creates isolated pixels that don't
//      match their neighbors, but these should average out.  The virtue
//      of this approach (apart from its simplicity) is that it should
//      be immune to false edges - local spikes due to noise - that
//      might fool the algorithms that explicitly look for edges.  In
//      practice, though, it seems to be even more sensitive to noise
//      than the other algorithms, probably because it treats every pixel
//      as independent and thus doesn't have any sort of inherent noise
//      reduction from considering relationships among pixels.
//

// assembler routine to scan for an edge using "mode 2" (maximum slope)
extern "C" int edgeScanMode2(const uint8_t *pix, int npix, const uint8_t **edgePtr, int dir);

// PlungerSensor interface implementation for edge detection setups.
// This is a generic base class for image-based sensors where we detect
// the plunger position by finding the edge of the shadow it casts on
// the detector.
//
// Edge sensors use the image pixel span as the native position scale,
// since a position reading is the pixel offset of the shadow edge.
class PlungerSensorEdgePos: public PlungerSensorImage<int>
{
public:
    PlungerSensorEdgePos(PlungerSensorImageInterface &sensor, int npix)
        : PlungerSensorImage(sensor, npix, npix - 1)
    {
    }
    
    // Process an image - scan for the shadow edge to determine the plunger
    // position.
    //
    // If we detect the plunger position, we set 'pos' to the pixel location
    // of the edge and return true; otherwise we return false.  The 'pos'
    // value returned, if any, is adjusted for sensor orientation so that
    // it reflects the logical plunger position (i.e., distance retracted,
    // where 0 is always the fully forward position and 'n' is fully
    // retracted).

#if SCAN_METHOD == 0
    // Scan method 0: one-way scan; original method used in v1 firmware.
    bool process(const uint8_t *pix, int n, int &pos, int& /*processResult*/)
    {        
        // Get the levels at each end
        int a = (int(pix[0]) + pix[1] + pix[2] + pix[3] + pix[4])/5;
        int b = (int(pix[n-1]) + pix[n-2] + pix[n-3] + pix[n-4] + pix[n-5])/5;
        
        // Figure the sensor orientation based on the relative brightness
        // levels at the opposite ends of the image.  We're going to scan
        // across the image from each side - 'bi' is the starting index
        // scanning from the bright side, 'di' is the starting index on
        // the dark side.  'binc' and 'dinc' are the pixel increments
        // for the respective indices.
        int bi;
        if (a > b+10)
        {
            // left end is brighter - standard orientation
            dir = 1;
            bi = 4;
        }
        else if (b > a+10)
        {
           // right end is brighter - reverse orientation
            dir = -1;
            bi = n - 5;
        }
        else if (dir != 0)
        {
            // We don't have enough contrast to detect the orientation
            // from this image, so either the image is too overexposed
            // or underexposed to be useful, or the entire sensor is in
            // light or darkness.  We'll assume the latter: the plunger
            // is blocking the whole window or isn't in the frame at
            // all.  We'll also assume that the exposure level is
            // similar to that in recent frames where we *did* detect
            // the direction.  This means that if the new exposure level
            // (which is about the same over the whole array) is less
            // than the recent midpoint, we must be entirely blocked
            // by the plunger, so it's all the way forward; if the
            // brightness is above the recent midpoint, we must be
            // entirely exposed, so the plunger is all the way back.

            // figure the average of the recent midpoint brightnesses            
            int sum = 0;
            for (int i = 0 ; i < countof(midpt) ; sum += midpt[i++]) ;
            sum /= countof(midpt);
            
            // Figure the average of our two ends.  We have very
            // little contrast overall, so we already know that the
            // two ends are about the same, but we can't expect the
            // lighting to be perfectly uniform.  Averaging the ends
            // will smooth out variations due to light source placement,
            // sensor noise, etc.
            a = (a+b)/2;
            
            // Check if we seem to be fully exposed or fully covered.
            pos = a < sum ? 0 : n;
            
            // stop here with a successful reading
            return true;
        }
        else
        {
            // We can't detect the orientation from this image, and 
            // we don't know it from previous images, so we have nothing
            // to go on.  Give up and return failure.
            return false;
        }
            
        // Figure the crossover brightness levels for detecting the edge.
        // The midpoint is the brightness level halfway between the bright
        // and dark regions we detected at the opposite ends of the sensor.
        // To find the edge, we'll look for a brightness level slightly 
        // *past* the midpoint, to help reject noise - the bright region
        // pixels should all cluster close to the higher level, and the
        // shadow region should all cluster close to the lower level.
        // We'll define "close" as within 1/3 of the gap between the 
        // extremes.
        int mid = (a+b)/2;

        // Scan from the bright side looking, for a pixel that drops below the
        // midpoint brightess.  To reduce false positives from noise, check to
        // see if the majority of the next few pixels stay in shadow - if not,
        // consider the dark pixel to be some kind of transient noise, and
        // continue looking for a more solid edge.
        for (int i = 5 ; i < n-5 ; ++i, bi += dir)
        {
            // check to see if we found a dark pixel
            if (pix[bi] < mid)
            {
                // make sure we have a sustained edge
                int ok = 0;
                int bi2 = bi + dir;
                for (int j = 0 ; j < 5 ; ++j, bi2 += dir)
                {
                    // count this pixel if it's darker than the midpoint
                    if (pix[bi2] < mid)
                        ++ok;
                }
                
                // if we're clearly in the dark section, we have our edge
                if (ok > 3)
                {
                    // Success.  Since we found an edge in this scan, save the
                    // midpoint brightness level in our history list, to help
                    // with any future frames with insufficient contrast.
                    midpt[midptIdx++] = mid;
                    midptIdx %= countof(midpt);
                    
                    // return the detected position
                    pos = i;
                    return true;
                }
            }
        }
        
        // no edge found
        return false;
    }
#endif // SCAN_METHOD 0
    
#if SCAN_METHOD == 1
    // Scan method 1: meet in the middle.
    bool process(const uint8_t *pix, int n, int &pos, int& /*processResult*/)
    {        
        // Get the levels at each end
        int a = (int(pix[0]) + pix[1] + pix[2] + pix[3] + pix[4])/5;
        int b = (int(pix[n-1]) + pix[n-2] + pix[n-3] + pix[n-4] + pix[n-5])/5;
        
        // Figure the sensor orientation based on the relative brightness
        // levels at the opposite ends of the image.  We're going to scan
        // across the image from each side - 'bi' is the starting index
        // scanning from the bright side, 'di' is the starting index on
        // the dark side.  'binc' and 'dinc' are the pixel increments
        // for the respective indices.
        int bi, di;
        int binc, dinc;
        if (a > b+10)
        {
            // left end is brighter - standard orientation
            dir = 1;
            bi = 4, di = n - 5;
            binc = 1, dinc = -1;
        }
        else if (b > a+10)
        {
            // right end is brighter - reverse orientation
            dir = -1;
            bi = n - 5, di = 4;
            binc = -1, dinc = 1;
        }
        else
        {
            // can't detect direction
            return false;
        }
            
        // Figure the crossover brightness levels for detecting the edge.
        // The midpoint is the brightness level halfway between the bright
        // and dark regions we detected at the opposite ends of the sensor.
        // To find the edge, we'll look for a brightness level slightly 
        // *past* the midpoint, to help reject noise - the bright region
        // pixels should all cluster close to the higher level, and the
        // shadow region should all cluster close to the lower level.
        // We'll define "close" as within 1/3 of the gap between the 
        // extremes.
        int mid = (a+b)/2;
        int delta6 = abs(a-b)/6;
        int crossoverHi = mid + delta6;
        int crossoverLo = mid - delta6;

        // Scan inward from the each end, looking for edges.  Each time we
        // find an edge from one direction, we'll see if the scan from the
        // other direction agrees.  If it does, we have a winner.  If they
        // don't agree, we must have found some noise in one direction or the
        // other, so switch sides and continue the scan.  On each continued
        // scan, if the stopping point from the last scan *was* noise, we'll
        // start seeing the expected non-edge pixels again as we move on,
        // so we'll effectively factor out the noise.  If what stopped us
        // *wasn't* noise but was a legitimate edge, we'll see that we're
        // still in the region that stopped us in the first place and just
        // stop again immediately.  
        //
        // The two sides have to converge, because they march relentlessly
        // towards each other until they cross.  Even if we have a totally
        // random bunch of pixels, the two indices will eventually meet and
        // we'll declare that to be the edge position.  The processing time
        // is linear in the pixel count - it's equivalent to one pass over
        // the pixels.  The measured time for 1280 pixels is about 1.3ms,
        // which is about half the DMA transfer time.  Our goal is always
        // to complete the processing in less than the DMA transfer time,
        // since that's as fast as we can possibly go with the physical
        // sensor.  Since our processing time is overlapped with the DMA
        // transfer, the overall frame rate is limited by the *longer* of
        // the two times, not the sum of the two times.  So as long as the
        // processing takes less time than the DMA transfer, we're not 
        // contributing at all to the overall frame rate limit - it's like
        // we're not even here.
        for (;;)
        {
            // scan from the bright side
            for (bi += binc ; bi >= 5 && bi <= n-6 ; bi += binc)
            {
                // if we found a dark pixel, consider it to be an edge
                if (pix[bi] < crossoverLo)
                    break;
            }
            
            // if we reached an extreme, return failure
            if (bi < 5 || bi > n-6)
                return false;
            
            // if the two directions crossed, we have a winner
            if (binc > 0 ? bi >= di : bi <= di)
            {
                pos = (dir == 1 ? bi : n - bi);
                return true;
            }
            
            // they haven't converged yet, so scan from the dark side
            for (di += dinc ; di >= 5 && di <= n-6 ; di += dinc)
            {
                // if we found a bright pixel, consider it to be an edge
                if (pix[di] > crossoverHi)
                    break;
            }
            
            // if we reached an extreme, return failure
            if (di < 5 || di > n-6)
                return false;
            
            // if they crossed now, we have a winner
            if (binc > 0 ? bi >= di : bi <= di)
            {
                pos = (dir == 1 ? di : n - di);
                return true;
            }
        }
    }
#endif // SCAN METHOD 1

#if SCAN_METHOD == 2
    // Scan method 2: scan for steepest brightness slope.
    virtual bool process(const uint8_t *pix, int n, int &pos, int& /*processResult*/)
    {        
        // Get the levels at each end by averaging across several pixels.
        // Compute just the sums: don't bother dividing by the count, since 
        // the sums are equivalent to the averages as long as we know 
        // everything is multiplied by the number of samples.
        int a = (int(pix[0]) + pix[1] + pix[2] + pix[3] + pix[4]);
        int b = (int(pix[n-1]) + pix[n-2] + pix[n-3] + pix[n-4] + pix[n-5]);
        
        // Figure the sensor orientation based on the relative brightness
        // levels at the opposite ends of the image.  We're going to scan
        // across the image from each side - 'bi' is the starting index
        // scanning from the bright side, 'di' is the starting index on
        // the dark side.  'binc' and 'dinc' are the pixel increments
        // for the respective indices.
        if (a > b + 50)
        {
            // left end is brighter - standard orientation
            dir = 1;
        }
        else if (b > a + 50)
        {
            // right end is brighter - reverse orientation
            dir = -1;
        }
        else
        {
            // can't determine direction
            return false;
        }

        // scan for the steepest edge using the assembly language 
        // implementation (since the C++ version is too slow)
        const uint8_t *edgep = 0;
        if (edgeScanMode2(pix, n, &edgep, dir))
        {
            // edgep has the pixel array pointer; convert it to an offset
            pos = edgep - pix;
            
            // if the sensor orientation is reversed, figure the index from
            // the other end of the array
            if (dir < 0)
                pos = n - pos;
                
            // success
            return true;
        }
        else
        {
            // no edge found
            return false;
        }

    }
#endif // SCAN_METHOD 2

#if SCAN_METHOD == 3
    // Scan method 0: one-way scan; original method used in v1 firmware.
    bool process(const uint8_t *pix, int n, int &pos, int& /*processResult*/)
    {        
        // Get the levels at each end
        int a = (int(pix[0]) + pix[1] + pix[2] + pix[3] + pix[4])/5;
        int b = (int(pix[n-1]) + pix[n-2] + pix[n-3] + pix[n-4] + pix[n-5])/5;
        
        // Figure the sensor orientation based on the relative brightness
        // levels at the opposite ends of the image.  We're going to scan
        // across the image from each side - 'bi' is the starting index
        // scanning from the bright side, 'di' is the starting index on
        // the dark side.  'binc' and 'dinc' are the pixel increments
        // for the respective indices.
        if (a > b+10)
        {
            // left end is brighter - standard orientation
            dir = 1;
        }
        else if (b > a+10)
        {
           // right end is brighter - reverse orientation
            dir = -1;
        }
        else
        {
            // We can't detect the orientation from this image
            return false;
        }
            
        // Figure the crossover brightness levels for detecting the edge.
        // The midpoint is the brightness level halfway between the bright
        // and dark regions we detected at the opposite ends of the sensor.
        // To find the edge, we'll look for a brightness level slightly 
        // *past* the midpoint, to help reject noise - the bright region
        // pixels should all cluster close to the higher level, and the
        // shadow region should all cluster close to the lower level.
        // We'll define "close" as within 1/3 of the gap between the 
        // extremes.
        int mid = (a+b)/2;

        // Count pixels brighter than the brightness midpoint.  We assume
        // that all of the bright pixels are contiguously within the bright
        // region, so we simply have to count them up.  Even if we have a
        // few noisy pixels in the dark region above the midpoint, these
        // should on average be canceled out by anomalous dark pixels in
        // the bright region.
        int bcnt = 0;
        for (int i = 0 ; i < n ; ++i)
        {
            if (pix[i] > mid)
                ++bcnt;
        }
        
        // The position is simply the size of the bright region
        pos = bcnt;
        if (dir < 1)
            pos = n - pos;
        return true;
    }
#endif // SCAN_METHOD 3
    
    
protected:
    // Sensor orientation.  +1 means that the "tip" end - which is always
    // the brighter end in our images - is at the 0th pixel in the array.
    // -1 means that the tip is at the nth pixel in the array.  0 means
    // that we haven't figured it out yet.  We automatically infer this
    // from the relative light levels at each end of the array when we
    // successfully find a shadow edge.  The reason we save the information
    // is that we might occasionally get frames that are fully in shadow
    // or fully in light, and we can't infer the direction from such
    // frames.  Saving the information from past frames gives us a fallback 
    // when we can't infer it from the current frame.  Note that we update
    // this each time we can infer the direction, so the device will adapt
    // on the fly even if the user repositions the sensor while the software
    // is running.
    virtual int getOrientation() const { return dir; }
    int dir;
       
    // History of midpoint brightness levels for the last few successful
    // scans.  This is a circular buffer that we write on each scan where
    // we successfully detect a shadow edge.  (It's circular, so we
    // effectively discard the oldest element whenever we write a new one.)
    //
    // We use the history in cases where we have too little contrast to
    // detect an edge.  In these cases, we assume that the entire sensor
    // is either in shadow or light, which can happen if the plunger is at
    // one extreme or the other such that the edge of its shadow is out of 
    // the frame.  (Ideally, the sensor should be positioned so that the
    // shadow edge is always in the frame, but it's not always possible
    // to do this given the constrained space within a cabinet.)  The
    // history helps us decide which case we have - all shadow or all
    // light - by letting us compare our average pixel level in this
    // frame to the range in recent frames.  This assumes that the
    // exposure level is fairly consistent from frame to frame, which 
    // is usually true because the sensor and light source are both
    // fixed in place.
    // 
    // We always try first to infer the bright and dark levels from the 
    // image, since this lets us adapt automatically to different exposure 
    // levels.  The exposure level can vary by integration time and the 
    // intensity and positioning of the light source, and we want
    // to be as flexible as we can about both.
    uint8_t midpt[10];
    uint8_t midptIdx;
    
public:
};


#endif /* _EDGESENSOR_H_ */