Bengali hand sign language recognition using convolutional neural networks
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
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| Jazyk: | English |
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BRAC University
2019
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| On-line přístup: | http://hdl.handle.net/10361/12282 |
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10361-12282 |
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10361-122822022-01-26T10:18:15Z Bengali hand sign language recognition using convolutional neural networks Rumi, Roisul Islam Hossain, Syed Moazzim Shahriar, Ahmed Islam, Ekhwan Arif, Hossain Islam, Md. Saiful Department of Computer Science and Engineering, Brac University Bangla Sign Language (BSL) CNN Deep learning Artificial intelligence Image processing Image processing. Artificial intelligence. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 27-29). Throughout the world the number of deaf and mute population is rising ever so increasingly. In particular Bangladesh has around 2.6 million individuals who aren't able to communicate with society using spoken language. Countries such as Bangladesh tend to ostracize these individuals very harshly thus creating a system that can allow them the opportunity to communicate with anyone regardless of the fact that they might know sign language is something we should pursue. Our system makes use of convolutional neural networks (CNN) to learn from the images in our dataset and detect hand signs from input images. We have made use of inception v3 and vgg16 as image recognition models to train our system with and without imagenet weights to the images. Due to the poor accuracy we saved the best weights after running the model by setting a checkpoint. It resulted in a improved accuracy. The inputs are taken from live video feed and images are extracted to be used for recognition. The system then separates the hand sign from the image and gets predicted by the model to get a Bangla alphabet as the result. After running the model on our dataset and testing it, we received an average accuracy of 99%. We wish to improve upon it as much as possible in the hopes to make deaf/mute communication with the rest of the society as e ortless as possible. Roisul Islam Rumi Syed Moazzim Hossain Ahmed Shahriar Ekhwan Islam B. Computer Science and Engineering 2019-07-01T06:43:01Z 2019-07-01T06:43:01Z 2019 2019-04 Thesis ID 15301033 ID 15301092 ID 15301119 ID 15301132 http://hdl.handle.net/10361/12282 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. 29 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Bangla Sign Language (BSL) CNN Deep learning Artificial intelligence Image processing Image processing. Artificial intelligence. |
| spellingShingle |
Bangla Sign Language (BSL) CNN Deep learning Artificial intelligence Image processing Image processing. Artificial intelligence. Rumi, Roisul Islam Hossain, Syed Moazzim Shahriar, Ahmed Islam, Ekhwan Bengali hand sign language recognition using convolutional neural networks |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. |
| author2 |
Arif, Hossain |
| author_facet |
Arif, Hossain Rumi, Roisul Islam Hossain, Syed Moazzim Shahriar, Ahmed Islam, Ekhwan |
| format |
Thesis |
| author |
Rumi, Roisul Islam Hossain, Syed Moazzim Shahriar, Ahmed Islam, Ekhwan |
| author_sort |
Rumi, Roisul Islam |
| title |
Bengali hand sign language recognition using convolutional neural networks |
| title_short |
Bengali hand sign language recognition using convolutional neural networks |
| title_full |
Bengali hand sign language recognition using convolutional neural networks |
| title_fullStr |
Bengali hand sign language recognition using convolutional neural networks |
| title_full_unstemmed |
Bengali hand sign language recognition using convolutional neural networks |
| title_sort |
bengali hand sign language recognition using convolutional neural networks |
| publisher |
BRAC University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12282 |
| work_keys_str_mv |
AT rumiroisulislam bengalihandsignlanguagerecognitionusingconvolutionalneuralnetworks AT hossainsyedmoazzim bengalihandsignlanguagerecognitionusingconvolutionalneuralnetworks AT shahriarahmed bengalihandsignlanguagerecognitionusingconvolutionalneuralnetworks AT islamekhwan bengalihandsignlanguagerecognitionusingconvolutionalneuralnetworks |
| _version_ |
1814308680091303936 |