TAILIEUCHUNG - Image retrieval by content using DCT and RGB projection

Image retrieval forms a major problem when a large database is considered. Image retrieval by content makes use of the available visual features of the image and helps in retrieving exactly the same image as that of the query image. For this purpose, the proposed work uses three different feature databases from SRM (Statistical Region Merging) algorithm and from DCT (Discrete Cosine Transform). | ISSN:2249-5789 P A Hemalatha et al , International Journal of Computer Science & Communication Networks,Vol 3(3), 134-140 Image Retrieval by content using DCT and RGB Projection Advanced Computing, School of Computing, SASTRA University, Tamil Nadu, India Abstract Image retrieval forms a major problem when a large database is considered. Image retrieval by content makes use of the available visual features of the image and helps in retrieving exactly the same image as that of the query this purpose, the proposed work uses three different feature databases from SRM (Statistical Region Merging) algorithm and from DCT (Discrete Cosine Transform). The similarity measurement is given by RGB projection which determines the size of the image and compares the images in the database with the query image. Keywords: CBIR, DCT, RGB projection. There exist various techniques for image retrieval. Traditional retrieval techniques used textual decriptors to search an image in the database which consumed much time and the users found it to be a difficult process since it required much processing. The other method which overcome the demerits of Keyword search is CBIR which uses the techniques of clustering and feature other name for CBIR is Query By Image Content which uses the features in the image for the process of retrieving similar of the features usually found in the images are color, shape and are various techniques used by CBIR to retrieve retrieval by CBIR is a combination of techniques by both features of low level and high level. This is carried out mainly to diminish the perception level of the user by analyzing the information of the accuracy of the system depends on the methods that are incorporated in feature extraction. The proposed work used three different features databases mainly using shape as the feature. Similarity phase of the

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