A Circular Object Detection Method Based on Digital Image
A technology for object detection and digital images, applied in image analysis, image data processing, instruments, etc., can solve the problems of consuming storage space, unsatisfactory fitting effect, and inability to distinguish noise points from composition targets
Active Publication Date: 2019-06-25
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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But there are also obvious shortcomings: (1) the amount of calculation is large, and the required calculation time is long
(2) It is necessary to pre-store the parameter space unit into the storage unit, which consumes a large amount of storage space
(3) Due to the discretization of image space and parameter space, the detection accuracy of Hough transform is not high
(4) The Hough transform uses a 1-value accumulation scheme to vote equally for all feature points, and cannot distinguish between noise points and feature points that make up the target
But there are also shortcomings: (1) Sensitive to noise, because it is a fitting algorithm, it will naturally try to make the fitting curve close to all the measured data, and when there is noise data, the fitting error will be large
When the measured object contains the edge data of the circle, the fitting accuracy is high and the speed is fast, but when there is background noise, the fitting effect is very unsatisfactory
(2) The least square method fits all points, and only one circle can be detected at a time
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[0069] In this embodiment, an axial circular object detection method based on digital images has accurate detection capabilities for multiple circular objects and partially obscured circular objects, and can be widely used in industrial circular workpiece detection and robotic circular detection. Object recognition and other fields have high application value. The steps include 1 obtaining the edge of the image; 2 dividing the edge into a connected one-way curve; 3 dividing the one-way curve into a quadratic curve; 4 determining the arc area; 5 circle fitting; figure 1 ,among them:
[0070] In the second step, the edges are divided into connected one-way curves. First, the depth-first traversal method is used to obtain the connected edge domains, and then the logical neighboring distance method (Logical Neighborhood Algorithm, LNA) is used according to the logical neighboring edge points. The distance divides the connected edge domain into multiple one-way connected curves.
[00...
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The invention discloses a circular object detection method based on a digital image, which is characterized by comprising the following steps: (1) getting the edge of an image; (2) segmenting the edge into a connected one-way curve; (3) segmenting the one-way curve into a secondary curve; (4) determining an arc; and (5) carrying out circle fitting. Through the method, multiple circular objects can be detected all at a time, and partially blocked circular objects can be detected. Detection is quick and highly precise. The method can be widely used in fields such as industrial circular work piece detection and robot-based circular object recognition, and is of high application value.
Description
Technical field [0001] The invention relates to a method for detecting a workpiece, in particular to a method for detecting a circular workpiece with a digital image. Background technique [0002] Circular object detection is a major focus of industrial inspection and robotics. In industrial production, many workpieces are round or spherical, such as bearings, balls, bottle caps, wheels, etc. The detection and positioning of these workpieces is very important of. The classic circle detection methods include Hough circle detection and least squares fitting algorithm based on edge tracking. [0003] The basic idea of the Hough circle detection algorithm is to transform a point in the image space to a curve or a curved surface in the parameter space, and the points with the same parameter feature will intersect in the parameter space after transformation. This is done by judging the degree of accumulation at the intersection. Characteristic curve detection. It is an effective met...
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IPC IPC(8): G06T7/60G06T7/13
CPCG06T7/60
Inventor谭治英周波吴晶华刘效
OwnerHEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI