Combined texture and shape features for content based image retrieval

被引：5
|
作者：
Mary Helta Daisy, M. [1 ]
Tamilselvi, S. [2 ]
Ginu Mol, J.S. [1 ]
机构：
[1] Dept of ECE, SXCCE, Chunkankadai, Kanyakumari Dist., Tamil Nadu, India
[2] Dept of ECE, National Engineering College, Kovilpatti, Tamil Nadu, India
来源：
Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2013 | 2013年
关键词：
Content-Based Image Retrieval - Euclidean distance - Fourier descriptors - Mean and standard deviations - Morphological closing operation - Precision-recall graphs - Retrieval accuracy - Retrieval performance;
D O I：
10.1109/ICCPCT.2013.6528956
中图分类号：
学科分类号：
摘要：
Image retrieval refers to extracting desired images from a large database. The retrieval may be of text based or content based. Here content based image retrieval (CBIR) is performed. CBIR is a long standing research topic in the field of multimedia. Here features such as texture & shape are analyzed. Gabor filter is used to extract texture features from images. Morphological closing operation combined with Gabor filter gives better retrieval accuracy. The parameters considered are scale and orientation. After applying Gabor filter on the image, texture features such as mean and standard deviations are calculated. This forms the feature vector. Shape feature is extracted by using Fourier Descriptor and the centroid distance. In order to improve the retrieval performance, combined texture and shape features are utilized, because many features provide more information than the single feature. The images are extracted based on their Euclidean distance. The performance is evaluated using precision-recall graph. © 2013 IEEE.
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页码：912 / 916
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