Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local...
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| Formato: | article |
| Lenguaje: | EN |
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Al-Khwarizmi College of Engineering – University of Baghdad
2005
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| Acceso en línea: | https://doaj.org/article/aaf93273bac64802a2e01cafc025b0db |
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| Sumario: | This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOMs were used and a comparison between the results from these SOMs was given.<br />The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20 people with six images for each person and a measure of the time differences between the methods is given.<br /> |
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