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Binarization Based Image Edge Detection Using Bacterial Foraging Algorithm

机译:基于二值化的图像边缘检测使用细菌觅食算法

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Bacterial Foraging Algorithm (BFA) is one of the powerful bio-inspired optimization algorithms which attempt to imitate the single and groups of E. Coli bacteria. In BFA algorithm, a set of bacteria try to forage towards a nutrient rich medium to get more nutrients. In this scheme, an objective function is posed as the effort or a cost incurred by the bacteria in search of food. In the present, an approach is presented for edge detection in a binarized image using bacterial foraging algorithm. .First binarization is applied to the input image to get an image matrix consisting of only the intensity values 0 and 255 of 8-bit image and then a swarm of bacteria are enthrusted on the binary image for extraction of edge information. Edges are detected by calculating the difference between intensity values of the present pixel with each of the neighboring eight pixels. Whenever the bacteria finds this intensity difference of 255 it will treat that pixel as its food and mark it as an edge pixel.
机译:细菌觅食算法(BFA)是强大的生物启发优化算法之一,试图模仿单一和组大肠杆菌细菌。在BFA算法中,一组细菌试图朝向营养丰富的培养基饲养以获得更多的营养。在该方案中,将目标函数作为努力或细菌搜索食物产生的成本。在本发明中,使用细菌觅食算法在二值化图像中呈现一种方法。 。第次二值化被应用于输入图像以获得由8位图像的强度值0和255组成的图像矩阵,然后在二进制图像上被吸引到群体的细菌以提取边缘信息。通过计算与每个相邻的八个像素的每个像素的强度值之间的差异来检测边缘。每当细菌发现这种强度差异255时,它将将该像素视为其食物并将其标记为边缘像素。

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