Pattern Recognition Using Clustering Method
Face recognition has become an important issue in many applications such as security systems, credit card verification and criminal identification. Face recognition is more secure in security system because facial image had been used as the ID. It also helps to avoid any duplicated identification. F...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2018
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| Online Access: | http://eprints.usm.my/53967/1/Pattern%20Recognition%20Using%20Clustering%20Method_Dharishaan%20Vengadesan_K4_2018.pdf |
| _version_ | 1825906991691726848 |
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| author | Vengadesan, Dharishaan |
| author_facet | Vengadesan, Dharishaan |
| author_sort | Vengadesan, Dharishaan |
| collection | USM |
| description | Face recognition has become an important issue in many applications such as security systems, credit card verification and criminal identification. Face recognition is more secure in security system because facial image had been used as the ID. It also helps to avoid any duplicated identification. Face recognition helps to recognize the facial image especially to indentifying certain criminals. Identifying and comparing faces in images is a very complex task, this is probably why it has attracted so many researchers in the latest years. Common method used in face recognition like eigenface method will be discussed. The objectives of this project are to design and develop a face recognition using MATLAB software beside to comprehend eigenfaces method of recognizing faces images. The face space is defined by the "eigenface", which are the eigenvectors of the set of faces, they do not necessarily correspond to isolated features such as eyes, ears and
noses. Eigenfaces approach seems to be an adequate method to be used in face recognition due to its simplicity, speed and learning capability. Experimental results are given to demonstrate the viability of the proposed face recognition
method. On the whole, when the system is modelled and tested, it was unreliable at times. The accuracy of the system was not high and has to be further improved. |
| first_indexed | 2024-03-06T15:57:41Z |
| format | Monograph |
| id | usm.eprints-53967 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2024-03-06T15:57:41Z |
| publishDate | 2018 |
| publisher | Universiti Sains Malaysia |
| record_format | dspace |
| spelling | usm.eprints-539672022-08-10T07:15:24Z http://eprints.usm.my/53967/ Pattern Recognition Using Clustering Method Vengadesan, Dharishaan T Technology TP Chemical Technology Face recognition has become an important issue in many applications such as security systems, credit card verification and criminal identification. Face recognition is more secure in security system because facial image had been used as the ID. It also helps to avoid any duplicated identification. Face recognition helps to recognize the facial image especially to indentifying certain criminals. Identifying and comparing faces in images is a very complex task, this is probably why it has attracted so many researchers in the latest years. Common method used in face recognition like eigenface method will be discussed. The objectives of this project are to design and develop a face recognition using MATLAB software beside to comprehend eigenfaces method of recognizing faces images. The face space is defined by the "eigenface", which are the eigenvectors of the set of faces, they do not necessarily correspond to isolated features such as eyes, ears and noses. Eigenfaces approach seems to be an adequate method to be used in face recognition due to its simplicity, speed and learning capability. Experimental results are given to demonstrate the viability of the proposed face recognition method. On the whole, when the system is modelled and tested, it was unreliable at times. The accuracy of the system was not high and has to be further improved. Universiti Sains Malaysia 2018-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53967/1/Pattern%20Recognition%20Using%20Clustering%20Method_Dharishaan%20Vengadesan_K4_2018.pdf Vengadesan, Dharishaan (2018) Pattern Recognition Using Clustering Method. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Kimia. (Submitted) |
| spellingShingle | T Technology TP Chemical Technology Vengadesan, Dharishaan Pattern Recognition Using Clustering Method |
| title | Pattern Recognition Using Clustering Method |
| title_full | Pattern Recognition Using Clustering Method |
| title_fullStr | Pattern Recognition Using Clustering Method |
| title_full_unstemmed | Pattern Recognition Using Clustering Method |
| title_short | Pattern Recognition Using Clustering Method |
| title_sort | pattern recognition using clustering method |
| topic | T Technology TP Chemical Technology |
| url | http://eprints.usm.my/53967/1/Pattern%20Recognition%20Using%20Clustering%20Method_Dharishaan%20Vengadesan_K4_2018.pdf |
| work_keys_str_mv | AT vengadesandharishaan patternrecognitionusingclusteringmethod |