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eSLID : entropy, saliency and steven's power law based local image descriptor for face recognition
| Content Provider | Indraprastha Institute of Information Technology, Delhi |
|---|---|
| Author | Goswami, Gaurav |
| Abstract | In biometrics and many other applications of image analysis, a primary requirement is to be able to compute the similarity, or dissimilarity, among images. This is achieved primarily by com- puting a feature vector for the image which is done using a feature description algorithm. The success of many automated algorithms that employ image processing methods depends heavily on the quality of the feature descriptor that is used. In this research, a novel image feature descriptor based on graph based visual saliency and entropy is proposed. The e ciency of the proposed algorithm is demonstrated using the problem of automated face recognition and a per- formance comparison is done with some popular existing feature descriptors. |
| File Format | |
| Language | English |
| Access Restriction | Authorized |
| Subject Keyword | Image analysis Face recognition Algorithms |
| Content Type | Text |
| Educational Degree | Bachelor of Technology (B.Tech.) |
| Resource Type | Thesis |
| Subject | Data processing & computer science |
