Acta Metrologica Sinica  2017, Vol. 38 Issue (3): 284-287    DOI: 10.3969/j.issn.1000-1158.2017.03.07
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Research on Image Retrieval Based on Kernel Density Estimation and Fractal Coding Algorithm
ZHANG Qin1,2,LIN Qing-hua1,2,KANG Xin1,2
1. Putian University, Putian, Fujian 351100, China 
2. Fujian Laser Precision Machining Engineering Technology Research Center, Putian, Fujian 351100, China
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Abstract  To improve the application value of image retrieval technology based on image fractal coding, aiming at natural images, a robust index (rotation, translation, scaling invariance) extracted from fractal parameters is proposed and that is improved Hu invariant moment. The index is extracted from an approximate image constructed by mean range blocks. Then combines statistic characteristic of fractal parameters with the Hu invariant moment index, the weighed indices are employed to compare the similarities among images. The experimental results show that the weighted indices perform better than a separate index.
Key wordsmetrology      image retrieval      variable bandwidth kernel density estimation      improved Hu invariant moment      fractal coding     
Received: 01 September 2016      Published: 19 April 2017
PACS:  TB96  
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ZHANG Qin
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ZHANG Qin,LIN Qing-hua,KANG Xin. Research on Image Retrieval Based on Kernel Density Estimation and Fractal Coding Algorithm[J]. Acta Metrologica Sinica, 2017, 38(3): 284-287.
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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2017.03.07     OR     http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2017/V38/I3/284
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