Piece Recognition

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Piece Recognition, (Chess Board or Chess Position Recognition) the ability of dedicated chess computers or chess playing robots to automatically recognize all the pieces on a chessboard, or in computer vision to convert an image of a real chessboard with pieces, or a chess diagram into a machine readable format specifying a chess position, such as Forsyth-Edwards Notation (FEN) or Extended Position Description (EPD).

=Computer Vision= Piece recognition is an interesting topic in computer vision, machine learning and pattern recognition using one or more cameras along with digital image processing and object recognition, more recently supported by deep learning techniques as demonstrated by Daylen Yang with his Chess ID project.

=Piece Recognition Boards= The user interface task to enter moves on a sensory board is often implemented with pressure sensitive or magnetic switches to determine origin and target squares with the implicit knowledge of the game state which piece was on the origin square and moved. The incremental update during game play starting from the initial position requires some care to keep internal and external board representation in sync, specially if analyzing with taking moves back. Here, real piece recognition offers not only much more comfort in entering arbitrary positions, but also more fault tolerant move recognition for dedicated units.

Piece recognition sensory boards require special electronics, and pieces with integrated passive components, such as piece type and piece color specific coils on ferrite core of a LC circuit. Selected via file- and rank multiplexer, the LC circuit forms a inductive coupled feedback loop of an amplifier forcing oscillation in piece type specific resonance, which could be measured or filtered, to detect the piece (if any) on the selected square. As reported by Robert Hyatt, Ken Thompson already had a piece recognition board based on coils in the base of the pieces, as demonstrated at ACM 1978 with Belle. Along with Henry S. Baird, Ken Thompson further contributed to computer vision applied to reading chess a few years later.

=Selected Systems=
 * Certabo Chessboard
 * Chess-Master
 * DGT Board
 * Mephisto Bavaria
 * Millennium ChessGenius
 * Raspberry Turk
 * Revelation II
 * TASC R30
 * TASC R40
 * TASC SmartBoard

=See also=
 * DGT Board - Piece Recognition
 * Pattern Recognition
 * Reading Chess
 * Robots
 * Sensory Board
 * TASC SmartBoard - Patent Infringement

=Publications=

2000 ...

 * Timothée Cour, Rémy Lauranson, Matthieu Vachette (2002). Autonomous Chess-playing Robot. École Polytechnique, pdf, pdf
 * David Urting, Yolande Berbers (2003). MarineBlue: A Low-Cost Chess Robot. Katholieke Universiteit Leuven, RA 2003. pdf

2010 ...

 * Arturo De la Escalera, Jose María Armingol (2010). Automatic Chessboard Detection for Intrinsic and Extrinsic Camera Parameter Calibration. Sensors, vol. 10, No. 3
 * Cynthia Matuszek, Brian Mayton, Roberto Aimi, Marc Peter Deisenroth, Liefeng Bo, Robert Chu, Mike Kung, Louis LeGrand, Joshua R. Smith, Dieter Fox (2011). Gambit: A Robust Chess-Playing Robotic System. Proc. of ICRA 2011, pdf
 * Nandan Banerjee, Debal Saha, Atikant Singh, Gautam Sanyal (2011). A Simple Autonomous Robotic Manipulator for Playing Chess Against any Opponent in Real Time. pdf
 * Cheryl Danner, Mai Kafafy (2015). Visual Piece Recognition. Stanford University, pdf
 * Raghuveer Kanchibail, Supreeth Suryaprakash, Suhas Jagadish (2016). Chess Board Recognition. School of Informatics and Computing, Indiana University, pdf

=Forum Posts=
 * Re: Tasc R30 v 2.5? by Steven Schwartz, CCC, September 08, 1999
 * Re: What happened to TASC? by Steven Schwartz, CCC, October 27, 2001
 * Web-cam based chessboard position digital recognition? by Clifton Prince, Chess.com, June 04, 2016

=External Links=
 * Patent US5129654 - Electronic game apparatus - Google Patents » TASC SmartBoard - Patent Infringement
 * Chess Grabber
 * Webcam Chess
 * Building Chess ID – Medium by Daylen Yang
 * GitHub - daylen/chess-id: Board localization and piece recognition by Daylen Yang
 * Visual Chess Recognition - Semantic Scholar by Cheryl Danner and Mai Kafafy

=References=

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