CONTENT BASED IMAGE RETRIEVAL (CBIR) OF FACE IMAGES IN WHT, DCT, DWT AND CT TRANSFORM DOMAIN

Applications of Content Based Image Retrieval (CBIR) are wide, such as : Crime Prevention, Security Check, Medical Diagnosis, Intellectual Property. This paper investigates the problem of CBIR of face images in transform domain. Face images that are similar to the query image are retrieved from the face database. Features of the face image are extracted in the spectrum domain of a selected transforms. These transforms are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Contourlet Transform (CT), and the proposed use of Walsh Hadamard Transform (WHT). For the performance analyses of features selection methods four face images databases are used. These are "Sheffield face database", "Olivetti Research Laboratory (ORL) face database", "Indian face Database", and "Georgia Tech (GT) face database". Euclidian and City block distance measures are analyzed to evaluate the performance of the retrieval process. The investigation concludes that, the retrieval rate is database dependent. But in general, the DWT is the best. On the other hand, the WHT is the best with respect to the speed of retrieving images. It is also shown that City Block distance measure gives results that are comparable with Euclidian distance measure, while it takes shorter execution time.