A Key Point Selection Shape Technique for Content Based Image Retrieval System
| Autor: | Pushpalatha S. Nikkam, B. Eswara Reddy |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Template matching Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering Pattern recognition 02 engineering and technology Object (computer science) Content-based image retrieval Identification (information) Robustness (computer science) Histogram 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Image retrieval |
| Zdroj: | International Journal of Computer Vision and Image Processing. 6:54-70 |
| ISSN: | 2155-6989 2155-6997 |
| DOI: | 10.4018/ijcvip.2016070104 |
| Popis: | Content Based Image Retrieval (CBIR) is the process of retrieving visually similar images from huge datasets. Images are identified based on their content. Content identification using shape features is considered in this paper. Content identification using shapes is a challenging task considering multiple variations observed in images, complex backgrounds and vast categories of contents. This paper describes a shape descriptor based CBIR system. The content of an image is identified using a key point based shape descriptor. Template matching techniques are adopted to accurately describe object shapes. The object shape identified is described using histogram vectors. The use of SVM classifier for content recognition and image retrieval task is considered. Results presented prove robustness of the key point technique to accurately describe object shapes even in complex images. Performance of the proposed system is compared with existing state of art systems. Results obtained and described in the paper prove a better performance of proposed CBIR system. |
| Databáze: | OpenAIRE |
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