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Proceedings Paper

Content-based butterfly image retrieval based on keyblock distribution
Author(s): Wei Song; Cheng Cai; Xiang Qin; Yu Meng; Huan Hao
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Paper Abstract

In the agricultural research area, the study about butterflies is very important. However, there is hardly any content-based butterfly image retrieval system. The text-based image retrieval system is not objective enough, and could not provide the characteristics of image content. Conventionally, the RGB color histogram-based image retrieval can't provide spatial features of images, and is easily affected by the pixel distribution, which is unable to represent the comprehensive characteristics of images. In this paper, we proposed a new butterfly image retrieval algorithm based on keyblock distribution. The keyblock-based image retrieval algorithm is a generalization of the technology in computer image retrieval area which is very advanced and useful. Our proposed butterfly image keyblock distribution extraction contains three procedures: first, a codebook with specific length is estimated by employing the vector quantization technique; second, the original butterfly image is divided into non-overlapping blocks; third, each block of butterfly image is encoded with the index number of codebook. From the keyblocks, we can extract both the color distribution information and the local spatial information of butterfly image. In the performance evaluation, experimental results show that in our retrieval system, average recall (AR) and average normalized modified retrieval rank (ANMRR) achieved 0.74 and 0.3291, respectively.

Paper Details

Date Published: 10 July 2009
PDF: 8 pages
Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 74890Q (10 July 2009); doi: 10.1117/12.836877
Show Author Affiliations
Wei Song, Northwest A&F Univ. (China)
Cheng Cai, Northwest A&F Univ. (China)
Xiang Qin, Northwest A&F Univ. (China)
Yu Meng, Northwest A&F Univ. (China)
Huan Hao, Northwest A&F Univ. (China)


Published in SPIE Proceedings Vol. 7489:
PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering
Honghua Tan; Qi Luo, Editor(s)

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