We present a line scan color vision system that detects aspect flaws occurring on the color surfaces of drinking glasses dec- orated due to an industrial silk-screen process. For this purpose, we have designed a specific image acquisition device based on a color line-scan camera. As the pattern printed on glasses slightly varies between two glasses successively produced, flaw detection by color image analysis is a challenging problem. In order to overcome this problem, the aspect flaws detection is based on an original color image segmentation scheme that iteratively constructs pixel classes. Since the results of segmentation scheme are known to depend on the choice of the color space, the main originality of our approach is to automatically determine the most discriminant color space for each class to be constructed. Experimental results show that the selection of the well-suited color spaces contributes to improve the segmentation accuracy and the aspect flaw detection.