A Comparison Study on Image Content Based Retrieval Systems

Authors : Saed Alqaraleh, Hersh HAMA

Pages : 103-116

View : 44 | Download : 12

Publication Date : 2018-12-28

Article Type : Research Paper

Abstract :In recent years, multimedia searching has become an important research field. Multimedia files are one of the most important materials on the internet. Unfortunately, even for the state-of-the-art methods and applications based on accessing multimedia on the internet, it is hard to find the required files. The main purpose of this study is to investigate the performance of well-known image content-based retrieval techniques, i.e., Fuzzy Color and Texture Histogram insert ignore into journalissuearticles values(FCTH);, Edge Histogram Descriptor insert ignore into journalissuearticles values(EHD);, Scalable Color Descriptor insert ignore into journalissuearticles values(SCD);, Color Layout Descriptor insert ignore into journalissuearticles values(CLD);, Color and Edge Directivity Descriptor insert ignore into journalissuearticles values(CEDD);, and Speed-Up Robust Feature insert ignore into journalissuearticles values(SURF); combined with Fast Library Approximate Nearest Neighbor insert ignore into journalissuearticles values(FLANN);. In general, the objective of using these techniques is to find the query’s most relevant files and list them at the top of the retrieval list. Several experiments have been conducted and it has been observed that FCTH and SCD outperform other studied techniques. On the other hand, for the SURF combined with FLANN approach, the results of most of the queries were below user expectations. In addition, extracting the feature vectors using this method requires a massive amount of memory. Overall, none of the studied CBIR descriptors can be used individually to build a full image retrieval system. In our opinion, multiple descriptors can be used simultaneously to achieve a more robust system and accurate results.
Keywords : content based image retrieval techniques, re ranking algorithm, implicit ranking, multimedia search engines, information retrieval

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