A Robust Statistical Color Edge Detection for Noisy Images
سال انتشار: 1394
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 543
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شناسه ملی سند علمی:
JR_JIST-3-2_003
تاریخ نمایه سازی: 9 اسفند 1395
چکیده مقاله:
Edge detection plays a significant role in image processing and performance of high-level tasks such as image segmentation and object recognition depends on its efficiency. It is clear that accurate edge map generation is more difficult when images are corrupted with noise. Moreover, most of edge detection methods have parameters which must be set manually. Here we propose a new color edge detector based on a statistical test, which is robust to noise. Also, the parameters of this method will be set automatically based on image content. To show the effectiveness of the proposed method, four state-of-the-art edge detectors are implemented and the results are compared. Experimental results on five of the most well-known edge detection benchmarks show that the proposed method is robust to noise. The performance of our method for lower levels of noise is very comparable to the existing approaches, whose performances highly depend on their parameter tuning stage. However, for higher levels of noise, the observed results significantly highlight the superiority of the proposed method over the existing edge detection methods, both quantitatively and qualitatively.
کلیدواژه ها:
نویسندگان
Mina Alibeigi
Department of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Niloofar Mozafari
Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
Zohreh Azimifar
Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
Mahnaz Mahmoodian
Department of Electrical and Computer Engineering, University of Tehran, Tehran, Iran