Chinese Chess Recognition Based on Projection Histogram of Polar Coordinates Image and FFT

Abstract

The recognition of Chinese chess through computer vision includes chess detection and its character recognition, and the process should be fast and robust. In this paper, Robert operator is used to get the edge information of chess, then detection, localization and segmentation of the chess are realized through mathematical morphology and template circle method. A new algorithm based on projection histogram of polar coordinates image and Fast Fourier Transform is introduced to extract the rotation-invariant feature of chess characters. Experiments show that the algorithm can accurately recognize all chesses within 300 ms, and is robust to any rotation.