Noisy images edge detection: Ant colony optimization algorithm

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:

Ant Colony ، Edge Detection ، Gaussian Noise ، Noisy Image ، Salt and Pepper Noise

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.