Applying Genetic Algorithm for Optimizing the User Query in Image and Video Retrieval

In an information retrieval system, the query can be made by user sketch. The new method presented here, optimizes the user sketch and applies the optimized query to retrieval the information. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extraction. To optimize the retrieval process, one stage of retrieval is performed by the user sketch. The retrieval criterion is based on the proposed distance metric from the user query. Retrieved answers are considered as the primary population for evolutionary optimization. The optimized query may be achieved through reproducing and minimizing the proposed measurement by using Genetic algorithm (GA). The optimized query could then be used for the retrieval of concepts from a given Data Base (DB). The proposed algorithms are evaluated for trajectory retrieval from urban traffic surveillance video and image retrieval from a DB. Practical implementations have demonstrated the high efficiency of this system in trajectory retrieval and image indexing.