A New Local Descriptor Based on Strings for Face Recognition
This paper proposes the use of strings as a new local descriptor for face recognition. The face image is first divided into nonoverlapping subregions from which the strings (words) are extracted using the principle of chain code algorithm and assigned into the nearest words in a dictionary of visual...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/3451808 |
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| author | Hicham Zaaraoui Abderrahim Saaidi Rachid El Alami Mustapha Abarkan |
| author_facet | Hicham Zaaraoui Abderrahim Saaidi Rachid El Alami Mustapha Abarkan |
| author_sort | Hicham Zaaraoui |
| collection | DOAJ |
| description | This paper proposes the use of strings as a new local descriptor for face recognition. The face image is first divided into nonoverlapping subregions from which the strings (words) are extracted using the principle of chain code algorithm and assigned into the nearest words in a dictionary of visual words (DoVW) with the Levenshtein distance (LD) by applying the bag of visual words (BoVW) paradigm. As a result, each region is represented by a histogram of dictionary words. The histograms are then assembled as a face descriptor. Our methodology depends on the path pursued from a starting pixel and do not require a model as the other approaches from the literature. Therefore, the information of the local and global properties of an object is obtained. The recognition is performed by using the nearest neighbor classifier with the Hellinger distance (HD) as a comparison between feature vectors. The experimental results on the ORL and Yale databases demonstrate the efficiency of the proposed approach in terms of preserving information and recognition rate compared to the existing face recognition methods. |
| format | Article |
| id | doaj-art-c790741d462645b8ab53b5c79475d60a |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-c790741d462645b8ab53b5c79475d60a2025-02-03T01:24:57ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552020-01-01202010.1155/2020/34518083451808A New Local Descriptor Based on Strings for Face RecognitionHicham Zaaraoui0Abderrahim Saaidi1Rachid El Alami2Mustapha Abarkan3LSI, Department of Mathematics, Physics and Computer Science, Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University, B.P. 1223, Taza, MoroccoLSI, Department of Mathematics, Physics and Computer Science, Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University, B.P. 1223, Taza, MoroccoLISAC Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, B.P. 1796, Atlas, Fez, MoroccoLSI, Department of Mathematics, Physics and Computer Science, Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University, B.P. 1223, Taza, MoroccoThis paper proposes the use of strings as a new local descriptor for face recognition. The face image is first divided into nonoverlapping subregions from which the strings (words) are extracted using the principle of chain code algorithm and assigned into the nearest words in a dictionary of visual words (DoVW) with the Levenshtein distance (LD) by applying the bag of visual words (BoVW) paradigm. As a result, each region is represented by a histogram of dictionary words. The histograms are then assembled as a face descriptor. Our methodology depends on the path pursued from a starting pixel and do not require a model as the other approaches from the literature. Therefore, the information of the local and global properties of an object is obtained. The recognition is performed by using the nearest neighbor classifier with the Hellinger distance (HD) as a comparison between feature vectors. The experimental results on the ORL and Yale databases demonstrate the efficiency of the proposed approach in terms of preserving information and recognition rate compared to the existing face recognition methods.http://dx.doi.org/10.1155/2020/3451808 |
| spellingShingle | Hicham Zaaraoui Abderrahim Saaidi Rachid El Alami Mustapha Abarkan A New Local Descriptor Based on Strings for Face Recognition Journal of Electrical and Computer Engineering |
| title | A New Local Descriptor Based on Strings for Face Recognition |
| title_full | A New Local Descriptor Based on Strings for Face Recognition |
| title_fullStr | A New Local Descriptor Based on Strings for Face Recognition |
| title_full_unstemmed | A New Local Descriptor Based on Strings for Face Recognition |
| title_short | A New Local Descriptor Based on Strings for Face Recognition |
| title_sort | new local descriptor based on strings for face recognition |
| url | http://dx.doi.org/10.1155/2020/3451808 |
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