Document Details

Document Type : Thesis 
Document Title :
Extracting Tawaf Parameters Using Video Analysis Techniques
استخراج معاملات الطواف باستخدام تقنيات تحليل الفيديو
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : Hajj and Umrah are important for every Muslim, every year people from around the word visits Makkah to perform Hajj and Umrah. Tawaf is one of the most important pillars of Hajj and Umrah, which is characterized by severe congestion because of the large numbers of Muslims doing it concurrently in a limited place. One of Saudi 2030 vision aims is to increase the capacity of pilgrims to 30 million. To manage this huge number of pilgrims is a huge challenge for the management team to ensure the safety of people, to resolve the issue related to the crowd, management team always conveys the specific information about the number of people and their density. It is a challenging task to extract this information from this huge crowd. It requires simultaneous analysis of the videos frame by frame. It is not always easy to count the people who visit Makkah and make arrangement according it, to make safe and secure arrangements, management team always look into videos. Based on the foregoing, we need to more research to control pilgrims to make them perform their rituals easily and conveniently and save them from scramble and congestion. Many computer vision techniques allow extracting such information without the requirement for specific devices or manual processing. These proposed techniques involve methods to detect the moving bulk of pilgrims. In our thesis several methods are proposed to detect people; First we use Superpixels clustering method to split the image frame into large pixels and apply (SURF) extraction features and then (MSER) extraction features to find the number of people and apply frames differencing to detect the count of people who move and who stay not moving at a fixed place. Gabor filter is used to find the empty spaces at Mataf. Results show 10% in average of the percentage of error .As per the arrangement it can be said that this methods working properly to get good results. 
Supervisor : Dr. Muhammad Yahya Hassan gone 
Thesis Type : Master Thesis 
Publishing Year : 1441 AH
2020 AD 
Co-Supervisor : Dr. Gabriel Al-Amin Abu Samra 
Added Date : Wednesday, June 17, 2020 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
هاجر هليل الجهنيAljehani, Hajer HelailResearcherMaster 

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