Dice Recognition in Uncontrolled Illumination Conditions by Local Invariant Features

Abstract

A system is proposed for the recognition of the number of the dots on dice in general table game settings. Different from previous dice recognition systems which use a single top-view camera and work only under controlled illumination, the proposed one uses multiple cameras and works for uncontrolled illumination. Under controlled illumination edges are the prominent features considered by most approaches. But strong specular reflection, often observed in uncontrolled illumination, paralyzes the approaches solely based on edges. The proposed system exploits the local invariant features robust to illumination variation and good for building homographies across multi-views. The homographies are used to enhance coplanar features and weaken non-coplanar features, giving a way 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 applied for its consistency rendering local interest regions across large illumination variation. Experiments show that the proposed system can achieve a superb recognition rate in various uncontrolled illumination conditions.