Today, image data exist with extremely diverse visual and semantic content, and it is rapidly growing in size. This created innumerable possibilities and hence considerations for real-world image search system designers. Manual annotation of images with keywords describing the image content can make it easier to find images of interest, but this takes more time, making this approach very costly [1,2]. Thus, searching in image collection based on visual content is potentially a very powerful technique. CBIR uses visual contents of an image to search the desired images.It deals with the fundamental problem to mathematically describe the image content (image signature) and then, assessing the similarity between a pair of images based on their signatures. Inspite of the apparent simplicity of this, there are significant obstacles that need to be overcome in order to design an efficient CBIR system

CBIR, RANSAC, Dynamic Programming, Image Retrieval