TARGET RECOGNITION WITH COLOR COMPONENTS AND SOBEL OPERATOR

Year 2012, Volume: 2 Issue: 4, 305 - 310, 01.12.2012

Sertan Akarlar Mustafa Yagımlı

Abstract

The present study aims to develop a target recognizing software by comparing the image obtained through the camera and the images in the data base using a SOBEL operator and color components which are used to detect the shapes of objects. In the developed target recognition system, the image obtained through the camera and the images in the data base are first compared via SOBEL operator in terms of their shapes, and in case that the images are equal or highly similar to the determined similarity percentage, their color components are compared. If this comparison also provides expected similarity percentages, the target is considered to be recognized, thus enabling the control of both the shape and the color of the target. C# programming language is used in the developed software

Keywords

Color Component, Target Recognition, Image Processing, SOBEL Operator

References

• Karasulu B., “Review and Evaluation of Well-Known for Moving Object Detection and Tracking in Videos”, Journal of Aeronautics and Space Technologies, Vol.4, No.4, pp.11-22, 2010.
• Yagimli M., Varol H.S., “Real Time Color Composition Recognition”, Journal of Naval Science and Engineering, Vol.5, No.2, pp.89-97, 2009.
• Peker M., Zengin A., “Real-Time Motion- Sensitive Scientific Research and Essays, Vol:5, No:15, pp.2044-2050, 2010. System”,
• Saravanakumar S., Vadivel A., Saneem Ahmed C.G., Multiple Human Object “Tracking using Backgroung Subtraction and Shadow International Conference on Signal and Image Processing, pp.79-84, 2010. Images”,
• Yamamoto S., Mae Y., Shirai Y., Miura J., “Realtime Multiple Object Tracking Based on Optical Flows”, Robotics and Automation, roceedings., pp.2328-2333, 1995.
• Chuang C.-H., Chao Y.-L., Li Z.-P., “Moving Object Segmentation and Tracking Using Classification Models”, IEEE International Symposium, pp.1-8, 2010. and Color
• Kass M., Witkin A., Terzoupolos D., “Snakes: International Journal of Computer Vision, vol.1, No. 4, pp.321-331.,1988. models”,
• Maziere M., Chassaingl F., Garrido L., Salembie P., “Segmentation and Tracking of Video Objects for a Content-Based Video Indexing Conference, pp.1191-1194, 2000. IEEE International N.Özgen,
• Trackıng", M.Sc. Thesis, Gazi University Institute of Science and Technology, August Based Target Wang L.W., Qin J.L., “Study on Moving Object Tracking Algorithm in Video Images”, The Eighth International Conference on Electronic Measurement and Instruments, pp.1-4, 2007.
• Pradabpet C., Ravinu N., Chivapreecha S., Knobnob B., Dejhan K., “An Efficient Filter Structure for Multiplierless Sobel Edge Detection”, Technologies in Intelligent Systems and Industrial Applications, pp.1-5.,2009. Lopez-Molina
• Barrenechea E., Jurio A., De Baets B., “Multiscale Edge Detection Based on The SOBEL Method”, IEEE, pp.1-6., 2011. H., Shushang Autonomous
• Algorithm Based on Multi-feature Fusion”, IEEE, pp.1-4., 2011. Object Recognition
• Gonzales C.G., Woods R.E., “Digital image processing, Principles of Distributed Database Systems”, Prentice Hall, New Jersey, 577-581,2002.