Blurring of inappropriate scenes in a video using image processing
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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| Jazyk: | English |
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Brac University
2019
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| On-line přístup: | http://hdl.handle.net/10361/12293 |
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10361-12293 |
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10361-122932022-01-26T10:15:55Z Blurring of inappropriate scenes in a video using image processing Islam, Rahat Shahriar Siddiqui, Raisa Roy, Dipta Uddin, Jia Department of Computer Science and Engineering, Brac University Artificial Neural Network Blurring LeNet Architecture Image processing 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 (page 42). Inappropriate scenes such as bloody scenes, nudity, gore, drugs, weapons etc. are considered inappropriate especially in a developing Muslim country like Bangladesh. In our country, such scenes are very discouraged for children, old people or heart patients. Thus, keeping these in mind we propose a model where these inappropriate scenes will be detected and blurred from any video stream. Moreover, the model also shows percentage of explicitly in an input video file. As a result, people playing the video will know beforehand whether they would want to watch it or not and parents will have a greater control on what their children are watching. For nudity detection, there will be fragmented human figures that will be extracted and then the fragments will be compared against a database to decide whether nudity is involved or not. If it is involved and exceeds a predetermined threshold, then the video will be considered as pornography that many people may not prefer to watch. Similarly, the extracted figures of objects or gore scenes will be compared against a database to know the percentage of inappropriate scene in a video. Bringing both the nudity and goriness under one roof, we named the term explicit and if a video is explicit, the user will have the option of knowing it from beforehand and blur out any portion from the video automatically by using our model. The accuracy of our model is 93% and the algorithm we have used in this paper is CNN. Rahat Shahriar Islam Raisa Siddiqui Dipta Roy B. Computer Science and Engineering 2019-07-02T06:42:45Z 2019-07-02T06:42:45Z 2019 2018-10 Thesis ID 15101055 ID 15101066 ID 14101247 http://hdl.handle.net/10361/12293 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. 42 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Artificial Neural Network Blurring LeNet Architecture Image processing |
| spellingShingle |
Artificial Neural Network Blurring LeNet Architecture Image processing Islam, Rahat Shahriar Siddiqui, Raisa Roy, Dipta Blurring of inappropriate scenes in a video using image processing |
| 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 Islam, Rahat Shahriar Siddiqui, Raisa Roy, Dipta |
| format |
Thesis |
| author |
Islam, Rahat Shahriar Siddiqui, Raisa Roy, Dipta |
| author_sort |
Islam, Rahat Shahriar |
| title |
Blurring of inappropriate scenes in a video using image processing |
| title_short |
Blurring of inappropriate scenes in a video using image processing |
| title_full |
Blurring of inappropriate scenes in a video using image processing |
| title_fullStr |
Blurring of inappropriate scenes in a video using image processing |
| title_full_unstemmed |
Blurring of inappropriate scenes in a video using image processing |
| title_sort |
blurring of inappropriate scenes in a video using image processing |
| publisher |
Brac University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12293 |
| work_keys_str_mv |
AT islamrahatshahriar blurringofinappropriatescenesinavideousingimageprocessing AT siddiquiraisa blurringofinappropriatescenesinavideousingimageprocessing AT roydipta blurringofinappropriatescenesinavideousingimageprocessing |
| _version_ |
1814308458563895296 |