Edge-reinforced color space maximally stable extremal region detection method

A technology of extreme value area and color space, applied in image data processing, instrumentation, computing, etc., can solve the problems of poor invariance of blur changes, etc., and achieve the effect of improving poor invariance, weakening the influence of blur changes, and enriching regional features

Inactive Publication Date: 2013-07-24
ZHEJIANG UNIV
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Problems solved by technology

[0004] In order to solve the above problems, the object of the present invention is to provide an edge-enhanced method for detecting the most stable extremum region in color space, which comprehensively utilizes the edge information and color information of the image, and re...

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  • Edge-reinforced color space maximally stable extremal region detection method
  • Edge-reinforced color space maximally stable extremal region detection method
  • Edge-reinforced color space maximally stable extremal region detection method

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[0035] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0036]On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0037] see figure 1 , which is a flow chart of the steps of an edge-enhanced color space most stable e...

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Abstract

The invention discloses an edge-reinforced color space maximally stable extremal region detection method which comprises the steps of using a multiscale probability of boundary (mPb) edge detection method to detect edges of a color image to obtain edge information and obtain distance a weighting coefficient according to the edge information and a distance conversion formula, calculating the surface characteristics and the distance value of difference between adjacent pixels in a color space, using the distance weighting coefficient to weight the distance value to obtain a final distance set, obtaining a distance threshold set according to the distribution situation of the final distance set, combining the adjacent pixels with the distance value smaller than the threshold to the same region by continuously increasing a distance threshold, and extracting regions with the size change rate reaching to the local minimum along with the change of the threshold as the maximally stable region characteristics. The edge-reinforced color space maximally stable extremal region detection method comprehensively uses edge information and color information of the image to further improve fuzzy mapping invariance in keeping the self invariance of the maximally stable extremal region to the greatest degree.

Description

technical field [0001] The invention belongs to the field of image local feature extraction, in particular to an edge-enhanced method for detecting the most stable extremum region in color space. Background technique [0002] Image local invariant features have become a research hotspot in the field of image processing and computer vision in recent years. After artificial intelligence and neural networks, it has once again ignited people's enthusiasm for machine intelligence research. The core of image local invariant feature research is "invariance", that is, when recognizing an object, no matter how far or near the object is, and whether the object is rotated or observed from different angles, it can Correctly identify the object. Common invariances include perspective invariance, scale invariance, rotation invariance, illumination invariance, affine invariance, etc., but so far there is no local feature that has all the above invariances, and general local features can o...

Claims

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Application Information

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IPC IPC(8): G06T7/40
Inventor 于慧敏潘能杰
Owner ZHEJIANG UNIV
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