ABSTRACT In recent years, many image retrieval systems based on color feature like fuzzy color histogram, have been applied in image retrieval systems based on content (CBIR). Most of this methods are not able to determine pixels accurate colors, especially in combined manner, and only determine whole distribution of color factor in image; therefore they are not efficient in image retrieval. We have suggested weight vector factor in trum fuzzy histogram in this paper to remove these problems. But these methods only demonstrate total distribution of color feature in image and do not consider any kind of place data, like relative positions of objects in image. Therefore do not prepare strong techniques for image retrievals with complex place ornament. since the edge pixels are important places in image and determine objects in an image and often similar images have similar backgrounds, we use competitive fuzzy edge finder algorithm which effectively categorizes image pixels into 5 classes ,including 4 edge classes in different directions and 1 background class. after categorizing pixels, feature vector for each class would be determined, that includes Trum fuzzy color histogram and place position. we compared our suggested method to fuzzy histogram method and compound neighborhood fuzzy entropy method with color _place feature, as tests results show high efficiency of our suggested method for image retrievals from COREL database, including 3000 images
