Region of Interest Extraction using Colour Based Methods on the CUAVE Database

Abstract

Region of interest (ROI) extraction is an important step in deriving vi-sual features for an audio-visual speech recognition system. Colour based segmentationoers the potential of computationally inexpensive algorithms for ROI selection. Thispaper presents a comparative study of two colour based techniques, one using hue andaccumulated dierence, the other chrominance. Results are presented for the CUAVEdatabase. The two methods achieved 69% and 72% correct ROI extraction. The exper-iment prompted investigation of a new method using a chrominance based accumulateddierence image. The new method achieved 79% correct ROI identication. The overallresults suggest that a dual approach using chrominance to locate the mouth region andonly employing an accumulated dierence image when signicant motion is not presentwould oer good robustness with lower computational cost.