A novel approach to face recognition using freeman chain code and nearest neighbor classifier
| Autor: | Hicham Zaaraoui, Samir El Kaddouhi, Mustapha Abarkan |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Chain code
Pixel Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Pattern recognition 02 engineering and technology Facial recognition system Set (abstract data type) Computer Science::Computer Vision and Pattern Recognition Face (geometry) Histogram 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing Visual Word Artificial intelligence business |
| Zdroj: | 2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS). |
| DOI: | 10.1109/isacs48493.2019.9068863 |
| Popis: | This paper proposes a novel approach to face recognition using freeman chain code as a feature extractor for face representation, and the nearest neighbor classifier for face matching. The face description stage starts with resizing, and then dividing the face image into non-overlapping sub-regions, then a set of chains (words) are extracted from each region, and assigned later into the nearest word in a Dictionary of Visual Words (DoVW). As a result, each patch is represented by a histogram of visual words. Finally, the histograms are assembled into one to describe the face image. Unlike the most of the existing methods, which require a mask around the treated pixel, our methodology depends on directional changes from the starting pixel, which allow us to obtain information on the local and also the more global structures. The face matching is performed by using the nearest neighbor classifier with Hellinger, Cosine, or Chi-square as the distances measure between histograms. Experimental results show which metrics perform well and demonstrate the efficiency of the proposed approach in terms of recognition rate compared to the other face recognition methods. |
| Databáze: | OpenAIRE |
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