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 TypeDr GradeEmail
وليد يحي خواجيkhawagi, Waleed yahyaResearcherMaster 

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