Content Based Image Retrieval Using Joint Descriptors

被引:0
作者
Hake, Jyoti [1 ]
Bharade, Prasad [1 ]
机构
[1] SGGS IE&T, Dept E&TC, Nanded 431606, India
来源
2016 INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2016年
关键词
Descriptor; DWT; CBIR; Feature; Extractor etc;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Content based image retrieval helps manipulators to retrieve pertinent images based on their contents. A consistent content-based feature extraction technique is required to meritoriously extract most of the information from the images. These important elements include color, texture, intensity or shape of the object inside image. Various descriptors required for extracting global and local features. It's easy to describe message in the image linguistically but it's difficult to do the same for machine applications. Combined descriptors like canny edge detector, Histogram and Discrete Wavelet Transform are used. Histogram extracts global features, wavelet transform extracts texture feature in four orientations(+/- 450 degrees, +/- 90 degrees and +/- 180 degrees). Histogram, Canny edge detector jointly used to form joint feature descriptor. Result shows that histogram as descriptor outperforms result with an efficiency of 75% with feature vector size of 1x6.
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页数:4
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