Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review

Ji, Jing; Gao, Tian; Zhang, Weichuan; Gao, Y. S.; Sun, Chen

doi:10.48550/arxiv.2106.07929

Cited by 2 publications

(2 citation statements)

References 208 publications

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“…The existing image edge detection methods still cannot accurately detect adjacent edge contours from an input image. Take a Chinese chessboard image [75] as an example, the edge detection results from the HED method [174] for this region are illustrated in Fig. 6(b).…”

Section: Some Future Challenges On Image Edge Detectionmentioning

confidence: 99%

A Novel Decision Mechanism for Image Edge Detection

Jing

Liu

et al. 2021

Intelligent Computing Theories and Application

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Edge detection is one of the most important and fundamental problems in the field of computer vision and image processing. Edge contours extracted from images are widely used as critical cues for various image understanding tasks such as image segmentation, object detection, image retrieval, and corner detection. The purpose of this paper is to review the latest developments on image edge detection. Firstly, the definition and properties of edges are introduced. Secondly, the existing edge detection methods are classified and introduced in detail. Thirdly, the existing widely used datasets and evaluation criteria for edge detection methods are summarized. Finally, future research directions for edge detection are elaborated.

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Section: Some Future Challenges On Image Edge Detectionmentioning

confidence: 99%

A Novel Decision Mechanism for Image Edge Detection

Jing

Liu

et al. 2021

Intelligent Computing Theories and Application

View full text Add to dashboard Cite

show abstract

“…In order to solve the problem of the missing direction of edge pixels, Scharcanski and Venetsanopoulos [29] proposed a method of edge detection using local direction operators. It is precisely because the directional information of edge pixels is essential and relevant in various image analysis tasks [30][31][32][33][34]. Furthermore, a color edge detection method based on edge rendering, which combines gradient and intelligent routing, was proposed [35].…”

Section: Introductionmentioning

confidence: 99%

M2GF: Multi-Scale and Multi-Directional Gabor Filters for Image Edge Detection

Li,

Bi,

Zhang

et al. 2023

Applied Sciences

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An image edge detection algorithm using multi-directional and multi-scale Gabor filters is proposed in this paper. The main merit of this method is that high edge detection accuracy can be obtained while maintaining noise robustness. The approach proposed in this paper consists of three procedures: firstly, the transformation to the CIE L*a*b* color space, which has a wide shading area and uniform distribution; secondly, under different scales, the edge feature information of the image is extracted from several different directions by Gabor filters, and a new edge strength map is obtained by feature fusion; thirdly, the new fused edge strength map is enhanced with local features, and a noise-resistant image edge detector is obtained under a novel hysteresis threshold calculation. The experiments illustrate that, compared to the methods involved, the designed edge detector outperforms by about 2% to 4%, and also shows competitive performance regarding the ability to handle noise.

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Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review

Abstract: Year References Venue Content Kitchen and Pattern Recognition Letters A survey on contour based corner detection Rosenfeld [42] algorithm till 1982. Deriche and IEEE Computer Vision and Pattern A survey on corner and vertex detectors.

Cited by 2 publications

References 208 publications

A Novel Decision Mechanism for Image Edge Detection

A Novel Decision Mechanism for Image Edge Detection

M2GF: Multi-Scale and Multi-Directional Gabor Filters for Image Edge Detection

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