Image retrieval using haar color descriptor incorporating with pruning techniques

This paper presents a content-based image retrieval system using a compact color descriptor (63-bit binary Haar color descriptor) incorporating with pruning techniques. The objective of pruning is to look for the candidate images similar to the query image from the database and ignore the rest that are not likely to the query image. Several statistical pruning criteria are experimented in order to achieve faster retrieval time while preserve good retrieval performance. After the pruning process, the descriptors of the candidate images are then matched with that of the query. The most similar images will be retrieved and ordered according to their distance to the query. The proposed technique is evaluated based on different sizes of the database. The experimental results show good retrieval performance over a variety of image collections.