Noisy images edge detection: Ant colony optimization algorithm
محل انتشار: مجله هوش مصنوعی و داده کاوی، دوره: 4، شماره: 1
سال انتشار: 1395
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 384
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شناسه ملی سند علمی:
JR_JADM-4-1_009
تاریخ نمایه سازی: 19 تیر 1398
چکیده مقاله:
The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy images with Gaussian noise and salt and pepper noise. As the image edge frequencies are close to the noise frequency band, the edge detection using the conventional edge detection methods is challenging. The movement of ants depends on local discrepancy of image’s intensity value. The simulation results compared with existing conventional methods and are provided to support the superior performance of ACO algorithm in noisy images edge detection. Canny, Sobel and Prewitt operator have thick, non continuous edges and with less clear image content. But the applied method gives thin and clear edges.
کلیدواژه ها:
نویسندگان
Z. Dorrani
Department of Electrical Engineering, Payame Noor University (PNU), Tehran, Iran.
M.S. Mahmoodi
Department of Computer Engineering, Payame Noor University (PNU), Tehran, Iran.