A Robust Statistical Color Edge Detection for Noisy Images
Journal Title: Journal of Information Systems and Telecommunication - Year 2015, Vol 3, Issue 2
Abstract
Edge detection is a fundamental tool that plays a significant role in image processing, and performance of high-level tasks such as image segmentation and object recognition depends on its efficiency. Therefore, edge detection is one of the well-studied areas in image processing and computer vision. However, 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. In recent years different approaches has been used to address these problems. 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.
Authors and Affiliations
Mina Alibeigi, Niloofar Mozafari, Zohreh Azimifar, Mahnaz Mahmoodian
Keywords
Related Articles
- EP ID EP185927
- DOI 10.7508/jist.2015.02.003
- Views 104
- Downloads 0
Target Tracking in MIMO Radar Systems Using Velocity Vector
The superiority of multiple-input multiple-output (MIMO) radars over conventional radars has been recently shown in many aspects. These radars consist of many transmitters and receivers located far from each other. In th...
Image Retrieval Using Color-Texture Features Extracted From Gabor-Walsh Wavelet Pyramid
Image retrieval is one of the most applicable image processing techniques which have been extensively used. Feature extraction is one of the most important procedures used for interpretation and indexing images in Conten...
A Hybrid Cuckoo Search for Direct Blockmodeling
As a way of simplifying, size reducing and making sense of the structure of each social network, blockmodeling consists of two major, essential components: partitioning of actors to equivalence classes, called positions,...
Mitosis detection in breast cancer histological images based on texture features using AdaBoost
Counting mitotic figures present in tissue samples from a patient with cancer, plays a crucial role in assessing the patient’s survival chances. In clinical practice, mitotic cells are counted manually by pathologists in...
A New Node Density Based k-edge Connected Topology Control Method: A Desirable QoS Tolerance Approach
This research is an ongoing work for achieving consistency between topology control and QoS guarantee in MANET. Desirable topology and Quality of Service (QoS) control are two important challenges in wireless communicati...