Abstract
Noise removal, Object detection and Edge identification in an image is an active research problem in Computer Vision, Machine Vision and Digital Image Processing (DIP). Edge detection is considered as one of the basic steps in the DIP for the detection of the object. Edge discovery of the object is one of the big challenges when we have an image with a complex and clutter background or image having a significant amount of noise. Due to the noise in an image their always be a chance of non-true edge generation. The traditional operator like sobel, robert, canny, prewitt, log is able to find the edge pixel but not shown the good result when we focus on a proper boundary and edge detection for the objects in noisy images. In this paper author's proposed a novel filter, which gives the good result in comparison of traditional operators in a qualitative or quantitative parameter. For experimental result analysis, a qualitative and quantitative comparison is done with another well-known operator like sobel, robert, prewitt etc. All experimental analysis is done with the randomly selected images from the MSRA dataset (Salient Object data-set). Noisy images are prepared by mixing the artificial noise using MATLAB with there default value of mean and variance and further these images are used to evaluate the performance of our proposed filter in presence of noise.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
