00000ctmaa22000003a 4500 UP-1685675941123923275 Buklod 20151013120104.0 aa rb |||1 u| ta 151013s xx d r |||| u| (iLib)UPTAC-00017720382 UPVTC eng LG 993.5 2011 C66 N43 Nicolasora, Jude Ivan Michael S. author. Beedgee an edge generation technique using the Artificial Bee Colony Algorithm Jude Ivan Michael S. Nicolasora; John Paul T. Yusiong, adviser. 2011. [4], 82 leaves illustrations. Undergraduate thesis (B.S. Computer Science) -- University of the Philippines, Tacloban. Edge detection is mathematical in nature; it can be computed linearly and is not unfathomable or indeterminate as it appears to be. However, the immense solution space of the problem may contain a better solution compared to the mathematically computed solution. The goal of this research is to find that existing best solution within given solution space. The proposed approach used by this paper covers two parts, the generation of the grayscale image and the generation of the threshold image. In generating the grayscale image, the contrast and brightness can be adjusted to cater a specified need. The grayscale image can also be normalized. Threshold image on the other hand uses the generated grayscale image in order to find the pixels representing the edges of the image. This preprocessing technique narrows the search space. The Artificial Bee Colony Algorithm, an algorithm for optimization, will be used in order to find the best solution in the search space narrowed by the threshold image. The results in the experiments showed the effectiveness of Beedgee in detecting the edges of different image types. Edge detection. Artificial Bee Colony Algorithm. Image processing. Yusiong, John Paul T. adviser. FI UP UPTAC UPTAC LG 993.5 2011 C66 N43 Thesis