Title :
Color and illumination invariant dice recognition
Author :
Hsu, Gee-Sern ; Peng, Hsiao-Chia ; Yeh, Shang-Min
Author_Institution :
Artificial Vision Lab., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
Abstract :
A system is proposed for automatic reading of the number of dots on dice in general table game settings. Different from previous dice recognition systems which recognize dice of a specific color using a single top-view camera in an enclosure with controlled settings, the proposed one uses multiple cameras to recognize dice of various colors posed in a wide range of viewing angle and under uncontrolled conditions. It is composed of three modules. Module-1 locates the dice using the gradient-conditioned color segmentation (GCCS), proposed in this paper, to segment dice of arbitrary colors from the background. Module-2 exploits the local invariant features good for building homographies across multiple views and lighting conditions. The homographies are used to enhance coplanar features and weaken non-coplanar features, giving a solution to segment the top faces of the dice and make up the features ruined by possible specular reflection. To identify the dots on the segmented top faces, an MSER detector is embedded in Module-3 for its consistency in locating the dot regions regardless of illumination and viewpoint variations. Experiments show that the proposed system performs satisfactorily in various test conditions.
Keywords :
feature extraction; gradient methods; image colour analysis; image segmentation; image sensors; lighting; object recognition; GCCS; MSER detector; color invariant dice recognition; coplanar features; gradient-conditioned color segmentation; homographies; illumination invariant dice recognition; lighting conditions; local invariant features; noncoplanar features; single top-view camera; table game settings; uncontrolled conditions; viewing angle; Cameras; Color; Detectors; Feature extraction; Image color analysis; Image edge detection; Lighting; Object recognition; foreground segmentation; invariant feature; local descriptor;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6377835