This paper presents a new feature descriptor, namely local extreme complete trio pattern （LECTP） for image retrieval application. The LECTP extracts complete extreme to minimal edge information in all possible direc...This paper presents a new feature descriptor, namely local extreme complete trio pattern （LECTP） for image retrieval application. The LECTP extracts complete extreme to minimal edge information in all possible directions using trio values. The LECTP integrates the local extreme sign trio patterns （LESTP） with magnitude local operator （MLOP） for image retrieval. The performance of the LECTP is tested by conducting three experiments on Corel-5 000, Corel-10 000 and MIT-VisTex color databases, respectively. The results after investigation show a significant improvement in terms of average retrieval precision （ARP） and average retrieval rate （ARR） as compared to the other state-of-the art techniques in content based image retrieval （CBIR）.展开更多
文摘This paper presents a new feature descriptor, namely local extreme complete trio pattern （LECTP） for image retrieval application. The LECTP extracts complete extreme to minimal edge information in all possible directions using trio values. The LECTP integrates the local extreme sign trio patterns （LESTP） with magnitude local operator （MLOP） for image retrieval. The performance of the LECTP is tested by conducting three experiments on Corel-5 000, Corel-10 000 and MIT-VisTex color databases, respectively. The results after investigation show a significant improvement in terms of average retrieval precision （ARP） and average retrieval rate （ARR） as compared to the other state-of-the art techniques in content based image retrieval （CBIR）.
