A novel block intensity comparison code for video classification and retrieval

Appropriate organization of video databases is essential for pertinent indexing and retrieval of visual information. This paper proposes a new feature called block intensity comparison code (BICC) for video classification and retrieval. Block intensity comparison code represents the average block intensity difference between blocks of a frame. The extracted feature is further processed using principal component analysis (PCA) to reduce the redundancy while exploiting the correlations between the feature elements. The temporal nature of video is modeled by hidden Markov model (HMM) with BICC as the features. It is found that, BICC outperforms other visual features such as edge, motion and histogram which are commonly used for video classification.