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IMPLEMENTING SKETCH-BASED IMAGE RETRIEVAL SYSTEM USING EDGE DETECTION AND SIFT ALGORITHM

Throughout the past few years, several researchers have introduced various methods and various algorithms for a precise and dependable sketch-based image retrieval system. In this paper, a proposed sketch-based image retrieval system is introduced. The framework goes over two phases: creating the sketch dataset phase and implementing SIFT (scale invariant feature transform) algorithm. The sketch dataset was created by selecting 100 colored image passed through canny edge detection operator. The system tends to enter a linebased/hand-drawing sketch and applies the SIFT algorithm to match between the input sketch and all sketches in the dataset. SIFT is one of the main efficient algorithms that are used to make description and matching, since it works on large keypoints. This system retrieves images depending on sketch image, and the result of matching will retrieve images that are approximate the entered sketch. The proposed system is assessed according to the measures that are utilized in detection, description and matching grounds, which are precision, recall and accuracy measures. The system showed (96 %) accuracy for line based sketches and (84%) for hand drawing where the detection was identical.