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Face Recognition from Video Image (Paperback): Lutfar Rahman Bagdadi, MD Khalilur Rahman Khan, Md. Maidul Islam Face Recognition from Video Image (Paperback)
Lutfar Rahman Bagdadi, MD Khalilur Rahman Khan, Md. Maidul Islam
R1,209 Discovery Miles 12 090 Ships in 10 - 15 working days

Face recognition technology analyzes the unique shape, pattern and positioning of the facial features. Face recognition is very complex technology and is largely software based. This Biometric Methodology establishes the analysis framework with tailored algorithms for each type of biometric device. Face recognition starts with a picture, attempting to find a person in the image. This can be accomplished using several methods including movement, skin tones, or blurred human shapes. The face recognition system locates the head and finally the eyes of the individual. Face recognition technologies have been associated generally with very costly top secure applications. Today the core technologies have evolved and the cost of equipments is going down dramatically due to the integration and the increasing processing power. Certain applications of face recognition technology are now cost effective, reliable and highly accurate. The natural use of face recognition technology is the replacement of PIN, physical tokens or both needed in automatic authorization or identification schemes. Additional uses are automation of human identification or role authentication.

Ceramic Tiles Surface Defect Detection and Classification (Paperback): Md. Maidul Islam, Md. Rakibul Islam, Lutfar Rahman... Ceramic Tiles Surface Defect Detection and Classification (Paperback)
Md. Maidul Islam, Md. Rakibul Islam, Lutfar Rahman Bagdadi
R1,209 Discovery Miles 12 090 Ships in 10 - 15 working days

Quality control is an important issue in ceramic tiles industry. On the other hand, maintaining the rate of production with respect to time is also a major issue in ceramic tile manufacturing. Again, price of ceramic tiles also depends on purity of texture, accuracy of color, shape etc. Considering this criteria, an automated defect detection and classification technique has been proposed in this report that can have ensured the better quality of tiles in manufacturing process as well as production rate. Our proposed method will play an important role in the ceramic tiles industries to detect defect and to control the quality of ceramic tiles. Again, this automated classification method helps us to acquire knowledge about the pattern of the defect within a very short time and also to decide about the recovery process so that the defected tiles may not be mixed with fresh tiles.

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