Neural network-based intelligent image analysis
In recent times, the use of digital cameras and mobile phones has been growing and this inexorably leads to a significant rise in the number of digital images. These diverse sources of images make the task of managing online image databases challenging. With broadband network becoming ubiquitous, se...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/10356/19314 |
| _version_ | 1811687128965316608 |
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| author | Liew, Chiat Loon. |
| author2 | Patra Jagdish Chandra |
| author_facet | Patra Jagdish Chandra Liew, Chiat Loon. |
| author_sort | Liew, Chiat Loon. |
| collection | NTU |
| description | In recent times, the use of digital cameras and mobile phones has been growing and this inexorably leads to a significant rise in the number of digital images. These diverse sources of images make the task of managing online image databases challenging. With broadband network becoming ubiquitous, searching through online image database will have to be efficacious as the usual practice of tagging thousands of images and searching manually are both unrealistic and time-consuming.
Content based image retrieval (CBIR) has become increasingly popular with numerous researches being done in this field. CBIR could be the key to solving the problem of manual image retrieval or the need to use text annotation on images. The main goal of a CBIR system is to identify closely matched images and return them to the user accurately in the shortest possible time. |
| first_indexed | 2024-10-01T05:11:24Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/19314 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:11:24Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-10356/193142023-03-03T20:56:36Z Neural network-based intelligent image analysis Liew, Chiat Loon. Patra Jagdish Chandra School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer applications In recent times, the use of digital cameras and mobile phones has been growing and this inexorably leads to a significant rise in the number of digital images. These diverse sources of images make the task of managing online image databases challenging. With broadband network becoming ubiquitous, searching through online image database will have to be efficacious as the usual practice of tagging thousands of images and searching manually are both unrealistic and time-consuming. Content based image retrieval (CBIR) has become increasingly popular with numerous researches being done in this field. CBIR could be the key to solving the problem of manual image retrieval or the need to use text annotation on images. The main goal of a CBIR system is to identify closely matched images and return them to the user accurately in the shortest possible time. Bachelor of Engineering (Computer Engineering) 2009-12-03T09:23:34Z 2009-12-03T09:23:34Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/19314 en Nanyang Technological University 55 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computer applications Liew, Chiat Loon. Neural network-based intelligent image analysis |
| title | Neural network-based intelligent image analysis |
| title_full | Neural network-based intelligent image analysis |
| title_fullStr | Neural network-based intelligent image analysis |
| title_full_unstemmed | Neural network-based intelligent image analysis |
| title_short | Neural network-based intelligent image analysis |
| title_sort | neural network based intelligent image analysis |
| topic | DRNTU::Engineering::Computer science and engineering::Computer applications |
| url | http://hdl.handle.net/10356/19314 |
| work_keys_str_mv | AT liewchiatloon neuralnetworkbasedintelligentimageanalysis |