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Deanship of Graduate Studies
Document Details
Document Type
:
Thesis
Document Title
:
An Optimized Content based Video Searching System
نظام أمثلي للبحث في الفيديو المعتمد على المحتوى
Subject
:
Faculty of Computing and Information Technology
Document Language
:
Arabic
Abstract
:
Video Contents Analysis (VCA) is a new research field that recently emerged .VCA is the processes that analyzes video to extract The desired knowledge and information .Contents may refer to motion ,color, background and objects such as a human face or a car, to mention a few. This thesis investigates the algorithms which were designed for video content analysis such as background, text, and speech and face detection. Those algorithms are on a process of continuous improvement. Algorithms related to background, text, speech and face detection has been analyzed. The most robust one has been identified. Convolutional Neural Network (CNN) which is one of the state-of-art technologies has been implemented in solving the face detection problems. A theoretical model has been designed for the process of face detection and an algorithm slightly modified from recent algorithm has been proposed.
Supervisor
:
Prof. Maher Ali Khemakhem
Thesis Type
:
Master Thesis
Publishing Year
:
1439 AH
2017 AD
Co-Supervisor
:
Dr. Reda Mohamed Salama Khalifa
Added Date
:
Monday, October 23, 2017
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
وليد يحي خواجي
khawagi, Waleed yahya
Researcher
Master
Files
File Name
Type
Description
42859.pdf
pdf
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