Subpixel edge detection of color images by principal axis analysis and moment-preserving principle

Cheng, Stone; Wu, Tsung-Liang

doi:10.1016/j.patcog.2004.08.016

Cited by 38 publications

(16 citation statements)

References 26 publications

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“…They obtained the final exact edges by computing four parameters of the edge model. After that, different methods based on Spatial-Gray Moment (SGM) were proposed [8][9][10]. Additionally, Cheng and Wu put the moment based method in color images [11].…”

Section: Introductionmentioning

confidence: 99%

Sub-pixel edge detection based on an improved moment

Zhang

2010

Image and Vision Computing

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Section: Introductionmentioning

confidence: 99%

Sub-pixel edge detection based on an improved moment

Zhang

2010

Image and Vision Computing

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“…There are various edge detectors capable of extracting edges to subpixel accuracy. Readers who are interested in the detail of subpixel edge detectors should refer to the references (Tabatabai and Mitchell, 1984;Nomura et al, 1991;Shan and Boon, 2000;Cheng and Wu, 2005). Unlike chain-code technique that sequentially records edges along an object's contour; the edges derived from spatial-moment edge detector do not form a continuous curve.…”

Section: Subpixel Edge Detection and Sortingmentioning

confidence: 99%

An effective corner detection method using subpixel edge detector and Gaussian filter

Chiou

Liang

2010

Sensor Review

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to develop an effective and reliable corner detection algorithm so as to extract all the desired corners successfully. In addition, the influences of edge detection method as well as smoothing technique on the overall performance of corner detection techniques are investigated. Design/methodology/approach -In this paper, an effective corner detection algorithm based on subpixel edge detector and Gaussian filter is presented. First, a subpixel accuracy edge detector is used rather than a pixel accuracy edge detector to detect edges. Second, B-splines approximation technique is used to eliminate the staircase effect of a digital curve. Third, curvature curve derived from the edges is smoothed by a Gaussian filter. Finally, statistical process control technique is applied to detect vertices. Findings -The results show that spatial-moment outperforms chain code as an edge detector. Furthermore, the Gaussian filter should be used to smooth curvature curve instead of smoothing the profile of an object, because the former provides greater impact on the corner detection results. Originality/value -In addition to object recognition, motion tracking and obstacle avoidance, the proposed method also has many important engineering and manufacturing applications such as dimensional measuring, reverse engineering, and machine vision-based computer numerical control (CNC) machining of polygonal sheet metal parts.

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“…Since we have no idea about whether p 1 is larger than p 2 or not. The relationship between p 1 and p 2 can be determined by a vertex counting method [5].…”

Section: A Edge Vertices Detection On Triangle Meshes Using Moment-pmentioning

confidence: 99%

“…The watermark is embedded by modifying a subset of carefully selected edge vertices to resist both geometric distortion and simplification attacks. The proposed method detects the watermarked edge vertices by performing the proposed 3D moment-preserving technique [5] on the 3D mesh model. The remainder of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

3D Triangular Mesh Watermarking for Copyright Protection Using Moment-Preserving

Kuo

Cheng

2009

2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing

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A new watermarking scheme on 3D triangular mesh models is proposed. Watermarks are embedded by modifying a subset of carefully selected edge vertices in order to resist attacks. A local geometrical disturbance on the selected edge vertices is used to embed the information without destroying the local connectivity. Edge vertices are detected using the proposed 3D moment-preserving technique. Edge vertices quantize into multiple classes where each of them is used to embed a watermark bit. Experimental results show that the proposed scheme is robust in resisting common attacks.

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Subpixel edge detection of color images by principal axis analysis and moment-preserving principle

Cited by 38 publications

References 26 publications

Sub-pixel edge detection based on an improved moment

Sub-pixel edge detection based on an improved moment

An effective corner detection method using subpixel edge detector and Gaussian filter

3D Triangular Mesh Watermarking for Copyright Protection Using Moment-Preserving

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