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Self-adaptive angular-point detection method based on image contour sharpness

A technology of corner detection and image contour, applied in the field of image processing, to achieve strong resistance to noise interference, simple and clear method, and good detection effect

Inactive Publication Date: 2012-11-21
SHANGHAI JIAOTONG UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage of Susan's corner detection is that it uses a fixed threshold, which is not suitable for general situations. It is necessary to use an adaptive threshold to improve this algorithm.

Method used

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  • Self-adaptive angular-point detection method based on image contour sharpness
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  • Self-adaptive angular-point detection method based on image contour sharpness

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Embodiment Construction

[0032] In order to better understand the technical solutions of the present invention, a further detailed description will be given below in conjunction with the accompanying drawings and embodiments.

[0033] The flow chart of the inventive method for image corner detection is as follows figure 1 As shown, after reading the image, the edge of the image is extracted, and the sharpness value of each point on the edge is calculated; for each edge, the sharpness threshold is calculated, and candidate corner points are extracted; protruding points on the edge are filtered out; adjacent candidates are merged corner.

[0034] Embodiments of the present invention are attached figure 1 The steps shown are carried out as follows:

[0035] 1. Read the image and extract the edge.

[0036] The raw image read as figure 2 As shown, the image is processed by the edge detection operator, and the binarized edge image is obtained as image 3 as shown, image 3 It is the rendering of the ...

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Abstract

The invention relates to a self-adaptive angular-point detection method based on image contour sharpness, which comprises the following steps of: firstly extracting an image edge by utilizing an edge detection operator, and computing the sharpness of each point on the edge; for each edge, selecting the point with the sharpness larger than a threshold value as a candidate angular point by using the mean value of the sharpness of all points on the edge as a threshold value; then projecting the fitting straight line of the candidate angular point towards a supporting edge in the supporting region of the candidate angular point, computing the distance between the candidate angular point and a projected point thereof, setting a threshold value for the distance, and filtering the points with sharpness smaller than the threshold value as projected points; and finally combining the candidate angular points into one angular point when a plurality of candidate angular points are abutted according to the principle that a connection weight value is maximum and of priority and the sharpness is maximum and secondary to obtain a final image angular point. The invention has high detection accuracy and strong anti-interference capability, can not detect a false angular point when detecting a round boundary and can be applied to the aspects of 3D reconstruction, visual positioning and measurement and the like.

Description

technical field [0001] The invention relates to an adaptive corner detection method based on image contour sharpness, which can be applied to optical flow calculation, motion estimation, target tracking, shape analysis, camera calibration, 3D reconstruction and the like. It belongs to the technical field of image processing. Background technique [0002] Corner is an important local feature of the image. While retaining the important feature information of the object in the image, the corner effectively reduces the amount of information data, which greatly reduces the amount of calculation when processing the image. Because the corner points concentrate a lot of important shape information on the image, the corner points are invariant to rotation, so the corner points are hardly affected by the lighting conditions. Corner extraction is of great significance in the fields of feature-based image registration, image understanding and pattern recognition. [0003] So far, a la...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 肖建力叶云王宸昊王斌刘允才
Owner SHANGHAI JIAOTONG UNIV
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