EDGE DETECTION TECHNIQUES FOR IMAGE SEGMENTATION

By M. R, M. Radha. 2011

706 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Various Image Segmentation Techniques: A Review (2014, methodology): “There are two basic techniques based on this method [3] [8] [26].”
Edge Detection Techniques for Image Segmentation - A Survey of Soft Computing Approaches (2009, methodology): “One convolution mask is then selected, namely that with the largest module[27].”
Learning to predict crisp boundaries (2018, methodology): “These traditional methods are often used as one of the fundamental features in many computer vision applications [4, 22, 23].”
Pixel Difference Networks for Efficient Edge Detection (2021, background): “boundaries play an important role in various higher-level computer vision tasks such as object recognition and detection [29, 11], object proposal generation [6, 54], image editing [10], and image segmentation [41, 4].”
A review of semantic segmentation using deep neural networks (2017, methodology): “For good overviews of the older pre-deep learning approaches, we refer the reader to several surveys [9,16–20] which cover the works spanning color and edge image segmentations to medical image understanding.”
A Comparison of various Edge Detection Techniques used in Image Processing (2012, background): “This noise should be filtered out before edge detection [8].”