Automated Image Processing for Scratch Detection on Specular Surfaces

2018-10-26
Okbay, Volkan
Akar, Gözde
Yaman, Ulaş

Suggestions

Automated image processing for scratch detection on specular surfaces
Okbay, Volkan; Akar, Gözde; Department of Electrical and Electronics Engineering (2018)
In industry, problems due to human error, mechanical flaws and transportation may occur; besides, they need to be detected in fast and efficient ways. In order to eliminate failure of human inspection, automated systems come in action, usually image processing involved. This thesis work, targets one common mass production problem on specular surfaces, i.e. scratch detection. To achieve this, we have implemented two different prototypes. The low-cost system is based on basic line detection, and the mid-end s...
Automated porosity measurement using image analysis techniques.
Hatiboğlu, Can Ulaş; Department of Petroleum and Natural Gas Engineering (2002)
Automated design analysis of anti-roll bars
Çalışkan, Kemal; Ünlüsoy, Yavuz Samim; Dağ, Serkan; Department of Mechanical Engineering (2003)
Automated detection of viewer engagement by head motion analysis
Güler, Uğur; Temizel, Alptekin; Department of Information Systems (2015)
Measuring viewer engagement plays a crucial role in education and entertainment. In this study we analyze head motions of the viewers from video streams to automatically determine their engagement level. Due to unavailability of a dataset for such an application, we have built our own dataset. By using face detection system, the head position of viewer is obtained throughout the video for each frame. Then, using these positions, we analyze and extract some features. In order to classify the data, we employ ...
Automated crowd behavior analysis for video surveillance applications
Güler, Püren; Temizel, Alptekin; Taşkaya Temizel, Tuğba; Department of Information Systems (2012)
Automated analysis of a crowd behavior using surveillance videos is an important issue for public security, as it allows detection of dangerous crowds and where they are headed. Computer vision based crowd analysis algorithms can be divided into three groups; people counting, people tracking and crowd behavior analysis. In this thesis, the behavior understanding will be used for crowd behavior analysis. In the literature, there are two types of approaches for behavior understanding problem: analyzing behavi...
Citation Formats
V. Okbay, G. Akar, and U. Yaman, “Automated Image Processing for Scratch Detection on Specular Surfaces,” 2018, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/82543.