Apparel coordination based on contour and dominant colours matching

The paper proposes a mobile application for clothing coordination, which could be of great benefit for stores and people seek for fashion advices. The application matches apparel image input with, previously saved apparel images, and then provides the user with the possible matching suggestions based on the apparel outline and dominating colors. For this purpose two Region of Interest (ROI) extraction components were developed, to facilitate apparel outline classification and color extraction. Two-level binary support vector machines were trained for apparel's classification into top, skirt or pair of trousers. K-means algorithm was used for recognizing the apparel's dominant colors. The colour matching is offered through analogous and complementary matching; K-nearest neighbor algorithm was adopted for this purpose. The application was developed and tested on Android 2.2 (Froyo) and the results showed that: (1) the application is able to classify apparels at high accuracy, (2) The proposed color recognition and matching strategies outperform the current ones.