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Content-based image retrieval with ordered dither block truncation coding features
- Source :
- ICIP
- Publication Year :
- 2013
- Publisher :
- IEEE, 2013.
-
Abstract
- This paper presents a technique for Content-Based Image Retrieval (CBIR) by exploiting the low complexity advantage of the Ordered-Dither Block Truncation Coding (ODBTC) for generating image content descriptors. The two image features, namely Color Co-occurrence Feature (CCF) and Bit Pattern Features (BPF), are generated from ODBTC encoded data streams (without really performing an image compression or decoding process) to measure the similarity between two images. Experimental results show that the proposed method is superior to the Block Truncation Coding (BTC) image retrieval system and other former methods, and prove that the ODBTC scheme is not only suited for image compression for its simplicity, but also offers a conveniently way for image indexing in the content-based image retrieval system.
- Subjects :
- Computer science
business.industry
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
Content-based image retrieval
Block Truncation Coding
Image texture
Feature (computer vision)
Computer vision
Dither
Visual Word
Artificial intelligence
business
Image retrieval
Feature detection (computer vision)
Data compression
Image compression
Color Cell Compression
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2013 IEEE International Conference on Image Processing
- Accession number :
- edsair.doi...........43b2bcd22ce32bc1f4776e662c15a587
- Full Text :
- https://doi.org/10.1109/icip.2013.6738825