Center symmetric local binary co-occurrence pattern for texture, face and bio-medical image retrieval

• A problem of content based image retrieval is considered.
• A local texture feature descriptor is proposed using local pattern and GLCM.
• The proposed method is tested on texture, face and medical image databases.
• For validation, the proposed method is compared to other local patterns.

Content based image retrieval is a common problem for a large image database. Many methods have been proposed for image retrieval for some particular type of datasets. In the proposed work, a new image retrieval technique has been introduced. This technique is useful for different kind of dataset. In the proposed method, center symmetric local binary pattern has been extracted from the original image to obtain the local information. Co-occurrence of pixel pairs in local pattern map have been observed in different directions and distances using gray level co-occurrence matrix. Earlier methods have utilized histogram to extract the frequency information of local pattern map but co-occurrence of pixel pairs is more robust than frequency of patterns. The proposed method is tested on three different category of images, i.e., texture, face and medical image database and compared with typical state-of-the-art local patterns.