Monitoring of endangered fish using image processing and AI tools
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
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| Формат: | Диссертация |
| Язык: | English |
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Brac University
2019
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| Online-ссылка: | http://hdl.handle.net/10361/12291 |
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10361-122912022-01-26T10:18:29Z Monitoring of endangered fish using image processing and AI tools Hossain, Naheen Habib, Ahsan Plabon, Tasharif Mehedi Uddin, Jia Department of Computer Science and Engineering, Brac University Image processing Endangered fish Object detection Image processing--Digital techniques. Machine learning. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 31-33). Marine life constitutes half of earth’s total biodiversity. But preservation and monitoring of them efficiently face setbacks largely due to technological limitations and economic reasons. Technological challenges include lack of effective image processing methods curtailed to underwater environment. Underwater image processing, object detection and classification have always been a challenge to accomplish through traditional methods. The methods including sonar radiation produces results, but they are nowhere near economical or accurate as intended. Alternatively, research has been conducted in solid and stationary object detection. Combining the knowledge of the already existing researches done in object detection, in this thesis, we compare performances of various classification algorithms using the data extracted from images of fishes taken in various luminous conditions. For this paper we will only consider large to medium sized fishes but exclude other non-chordate bio-life. The first step is to prepare the images for suitable feature extraction.The next step is to extract suitable features from the available images of the dataset.The next step is to classify the fishes through four different classifiers (SVM, KNN, NB and Random forest classifier) on the basis of the features we have extracted. Lastly we compare the relative performances of these classifiers. Naheen Hossain Ahsan Habib Tasharif Mehedi Plabon B. Computer Science and Engineering 2019-07-02T06:14:48Z 2019-07-02T06:14:48Z 2018 2018-12 Thesis ID 13101244 ID 15201047 ID 15101072 http://hdl.handle.net/10361/12291 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 33 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Image processing Endangered fish Object detection Image processing--Digital techniques. Machine learning. |
| spellingShingle |
Image processing Endangered fish Object detection Image processing--Digital techniques. Machine learning. Hossain, Naheen Habib, Ahsan Plabon, Tasharif Mehedi Monitoring of endangered fish using image processing and AI tools |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. |
| author2 |
Uddin, Jia |
| author_facet |
Uddin, Jia Hossain, Naheen Habib, Ahsan Plabon, Tasharif Mehedi |
| format |
Thesis |
| author |
Hossain, Naheen Habib, Ahsan Plabon, Tasharif Mehedi |
| author_sort |
Hossain, Naheen |
| title |
Monitoring of endangered fish using image processing and AI tools |
| title_short |
Monitoring of endangered fish using image processing and AI tools |
| title_full |
Monitoring of endangered fish using image processing and AI tools |
| title_fullStr |
Monitoring of endangered fish using image processing and AI tools |
| title_full_unstemmed |
Monitoring of endangered fish using image processing and AI tools |
| title_sort |
monitoring of endangered fish using image processing and ai tools |
| publisher |
Brac University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12291 |
| work_keys_str_mv |
AT hossainnaheen monitoringofendangeredfishusingimageprocessingandaitools AT habibahsan monitoringofendangeredfishusingimageprocessingandaitools AT plabontasharifmehedi monitoringofendangeredfishusingimageprocessingandaitools |
| _version_ |
1814308955736768512 |