Development of a real-time automated family classification system
The local binary pattern LBP, which was originally used for texture analysis, is now being proposed for improvement by the addition of threshold information. The LBP is superior in computational simplicity and this allows this project to be implemented in real time family classification system. As s...
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sg-ntu-dr.10356-453582023-07-07T16:51:59Z Development of a real-time automated family classification system Chen, George Fengrong. Teoh Eam Khwang School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision The local binary pattern LBP, which was originally used for texture analysis, is now being proposed for improvement by the addition of threshold information. The LBP is superior in computational simplicity and this allows this project to be implemented in real time family classification system. As such, this project has two main components, one is to access the performance of proposed LBP with thresholds information which is in the back end stage, and the other is to implement this in real time application which is in the front end stage. Accessing the performance of the thresholded LBP, in terms of its error rate and training time was experimented in this project. Experimental results showed that the thresholded LBP, with thresholds from -69 to +69, step size of 5, has an improved error rate of about 4% and the most significant improvements was 8% in the family classification experiment of 53x63 pictures. Bachelor of Engineering 2011-06-13T02:55:18Z 2011-06-13T02:55:18Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/45358 en Nanyang Technological University 89 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Chen, George Fengrong. Development of a real-time automated family classification system |
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The local binary pattern LBP, which was originally used for texture analysis, is now being proposed for improvement by the addition of threshold information. The LBP is superior in computational simplicity and this allows this project to be implemented in real time family classification system. As such, this project has two main components, one is to access the performance of proposed LBP with thresholds information which is in the back end stage, and the other is to implement this in real time application which is in the front end stage.
Accessing the performance of the thresholded LBP, in terms of its error rate and training time was experimented in this project. Experimental results showed that the thresholded LBP, with thresholds from -69 to +69, step size of 5, has an improved error rate of about 4% and the most significant improvements was 8% in the family classification experiment of 53x63 pictures. |
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Teoh Eam Khwang |
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Teoh Eam Khwang Chen, George Fengrong. |
format |
Final Year Project |
author |
Chen, George Fengrong. |
author_sort |
Chen, George Fengrong. |
title |
Development of a real-time automated family classification system |
title_short |
Development of a real-time automated family classification system |
title_full |
Development of a real-time automated family classification system |
title_fullStr |
Development of a real-time automated family classification system |
title_full_unstemmed |
Development of a real-time automated family classification system |
title_sort |
development of a real-time automated family classification system |
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2011 |
url |
http://hdl.handle.net/10356/45358 |
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1772826787976314880 |