Color is one of the most meaningful features used in content based retrieval of visual data. In video content based retrieval, color features computed on selected frames are integrated with other low-level features concerning texture, shape and motion in order to find clip similarities. For example, the Scalable Color feature defined in the MPEG-7 standard exploits HSV histograms to create color feature vectors. HSV is a widely adopted space in image and video retrieval, but its quantization for histogram generation can create misleading errors in classification of achromatic and low saturated colors. In this paper we propose an Enhanced HSV Histogram with achromatic point detection based on a single Hue and Saturation parameter that can correct this limitation. The enhanced histograms have proven to be effective in color analysis and they have been used in a system for automatic clip annotation called PEANO, where pictorial concepts are extracted by a clip clustering and used for similarity based automatic annotation.
Enhancing HSV Histograms with Achromatic Points Detection for Video Retrieval / Grana, Costantino; Vezzani, Roberto; Cucchiara, Rita. - STAMPA. - (2007), pp. 302-308. (Intervento presentato al convegno 6th ACM International Conference on Image and Video Retrieval (CIVR 2007) tenutosi a Amsterdam, The Netherlands nel Jul 9-11) [10.1145/1282280.1282327].