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Freeman chain code-based method for matching curves in digital image

A digital image and matching method technology, applied in the field of curve matching, can solve problems such as large amount of calculation, complex approximation calculation is difficult to realize, and does not use the geometric characteristics of curves, etc., to achieve the effect of small amount of calculation

Active Publication Date: 2010-12-15
南通丝乡丝绸有限公司 +1
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Problems solved by technology

At present, a lot of research has been done at home and abroad on the problem of curve matching. Some use semi-differential invariants for curve matching. This method needs to calculate the tangent vector of each point, which requires a large amount of calculation, and does not use the geometric characteristics of the curve; Splines are used for curve matching. This method uses splines to approximate curves, which determines its range; some people also propose to use straight line approximation for curve matching. transform matching problem

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  • Freeman chain code-based method for matching curves in digital image
  • Freeman chain code-based method for matching curves in digital image
  • Freeman chain code-based method for matching curves in digital image

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Embodiment Construction

[0042] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0043] Step 1: Freeman Chaincode

[0044] The digitized binary contour curve can be represented by the eight-direction Freeman chain code, and the eight-direction Freeman chain code is eight kinds of possible direction values ​​of the connection between two adjacent pixels, such as figure 2 shown. A curve is discretized by the grid to form n chains, and the chain code of this curve can be expressed as {c(i)} n , each chain points to one of eight directions, c(i) ∈ {0, 1, ... 7}, i is the index value of the pixel, c(i) is from pixel (i) to pixel ( The direction chain code of i+1), such as image 3 shown. For example, if the current pixel is p(i), b 7 is the next pixel on the curve, then the value of p(i) is 7. The curve matching algorithm proposed in this paper is based on this encoding method.

[0045] Step 2: Detection of the corner point of the freeman ...

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Abstract

The invention relates to a Freeman chain code-based method for matching curves in a digital image, which is technically characterized by comprising the following steps of: encoding a characteristic curve with eight-direction Freeman chain codes first; detecting corner points of the curves by adopting a difference accumulated value and three-point chain code difference-based method for detecting the corner points of Freeman chain code curves; calculating the starting points and direction of the curves of a detected corner point sequence according to corner point distance information and information on the included angles between the midpoints of straight-line portions among the corner points and midpoints of the curves; rearranging the detected corner point sequence according to the starting points and direction of the curves to obtain a corner point sequence which is not changed with the rotation, translation and dimension change of the curves; and calculating a length sequence of the corner points and an included angle sequence of the corner points according to the corner point sequence, and performing similar judgment on the two curves through the length sequence of the corner points and the included angle sequence of the corner points to match the curves. The method has the advantages of no influence of rotation, scaling and translation of the curves, small calculated amount and easy realization, and is a practical method for matching the curves.

Description

technical field [0001] The invention relates to a curve matching method in a digital image, in particular to an image matching and recognition in a digital image based on a Freeman chain code, which is suitable for matching operations among rotation, scaling and translation curves. Background technique [0002] Object recognition is a very important field in image processing. One of the methods of object recognition is to extract the characteristic curves of objects, and then match these characteristic curves to complete object recognition. At present, a lot of research has been done at home and abroad on the problem of curve matching. Some use semi-differential invariants for curve matching. This method needs to calculate the tangent vector of each point, which requires a large amount of calculation, and does not use the geometric characteristics of the curve; Splines are used for curve matching. This method uses splines to approximate curves, which determines its range; so...

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Application Information

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IPC IPC(8): G06T7/00G06K9/00
Inventor 郭雷余博赵天云韩军伟
Owner 南通丝乡丝绸有限公司
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