A traditional fashion designer has to draw a large number of drafts in order to accomplish an ideal style. Better performance can be achieved if these operations are done on computers, because the designer can easily make changes for various patterns and colors. To develop a computer-aided fashion design system, one of the most difficult tasks is to automatically separate the clothing from the background so that a new item can be ‘put on’. One difficulty of the segmentation work arises from the diverse patterns on the clothing, especially with folds or shadows. In this study, circular histograms are first utilized to quantize color and to reduce shadow/highlight effects. Then a color co-occurrence matrix and a color occurrence vector are proposed to characterize the color spatial dependence and color occurrence frequency of the clothing's texture. Next, based on the two color features blocks on the clothing are found by a region growing method. Finally, post-processing is applied to obtain a smooth clothing boundary. Experimental results are presented to show the feasibility of the proposed app
