OPTIMASI KOLONI SEMUT UNTUK FASE DETEKSI PERUBAHAN GARIS PADA SEGMENTASI CITRA - DESI NOVIANTI (Faktor Exacta, 2015)
Image is two-dimensional images generated from analog images into a continuous two-dimensional discrete image through the sampling process. Image processing can be easily processed, then the image will be split into segments in order to get the desired image only. Image segmentation is the process of separating objects with other objects in an image into objects based on certain characteristics. The segmentation process stops when objects have been observed. Variety of approaches have been developed to solve the problem of image segmentation. One of them with ant colony optmization (ACO). ACO was first introduced by M. Dorigo (Dorigo et al., 1996). One of the basic ideas of the ACO approach is to use the counter part of the trail pheromones used by ants as a medium of communication and as an indirect form of memory solutions previously found. To image segmentation, ACO algorithm is applied in the phase of a complex line change detection on phase change thermography. This section we apply the (Active Countur Models / ACM) based on ACO algorithm for segmentation of sub-images, which converts image segmentation searching for the best path problem in a restricted area. The results of this experiment will show that the algorithm changes the contour phase, will produce a phase of active contours and good so get a better image segmentation. Keyword: image, image Cementation, Optimization Ants, edge Detection