Face recognition using eigen-face implemented on dsp professor /
This thesis focus to develop an automatic face recognition using holistic features extracted that use the global features represented by low frequency data from face image. Holistic features are extracted using eigenface method where a linear projection technique such as PCA is used to capture the i...
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| Format: | Thesis Book |
| Language: | English |
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Perlis, Malaysia
School of Computer and Communication Engineering, Universiti Malaysia Perlis
2014
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| Online Access: | Click here to view full text content |
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| Summary: | This thesis focus to develop an automatic face recognition using holistic features extracted that use the global features represented by low frequency data from face image. Holistic features are extracted using eigenface method where a linear projection technique such as PCA is used to capture the important information in the image. Face image has low frequency information such as shape of mouth, eye, and nose which has high discrimination power. By using PCA, only several number of eigenvector is preserved which belong to these features. |
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| Physical Description: | xix, 131 pages colour illustration 30 cm. |
| Bibliography: | Includes bibliographical references. |