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Ellipse rapid detection method based on geometric constraint

A detection method and geometric constraint technology, applied in the field of computer vision, can solve the problems of low computational efficiency, large computational load, large cardinality, etc., to achieve the effect of implementing algorithms, ensuring classification accuracy, and reducing operations

Active Publication Date: 2016-09-07
DALIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

This type of method can improve the accuracy of ellipse detection to a certain extent, but it is greatly affected by occlusion. In addition, due to the huge base of points, it is inevitable that there will still be a large amount of calculation
Other improvement methods are also trying to filter some combinations of points or arcs that do not belong to the same ellipse, but generally need to calculate the parameters of the ellipse, so the calculation efficiency is still very low

Method used

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  • Ellipse rapid detection method based on geometric constraint
  • Ellipse rapid detection method based on geometric constraint
  • Ellipse rapid detection method based on geometric constraint

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Embodiment 1

[0056] 1. Preprocess the real image and extract edge point information. Using existing image processing tools (such as image grayscale processing, median filter, Gaussian blur method, Canny edge extraction method) to obtain more accurate coordinate information of edge points from RGB color image data for the input image.

[0057] 1-1 Convert the image into a grayscale image. Such as figure 1 shown.

[0058] 1-2 Perform median filtering on the grayscale image, since this method is an arc-based ellipse extraction method. Median filtering can reduce the noise points of segmented arcs.

[0059] 1-3 Use the Canny edge extraction method to extract edge point information (x i ,y i ,tan(θ i )),Such as figure 2 shown. Among them, the upper left point in the image coordinate system is (0,0), the downward is the x axis, and the right is the y axis. (x i ,y i ) is the edge point coordinates, is the edge point (x i ,y i ) gradient. This step just gets some unordered collecti...

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Abstract

The invention discloses an ellipse rapid detection method based on geometric constraint. The method employs a characteristic number to screen a combination of arcs which definitely do not belong to the same ellipse before the ellipse fitting, reduces the unnecessary ellipse fitting operation, and achieves the algorithm acceleration. The method solves a problem that the consumed time is longer in the prior art, and guarantees the ellipse detection accuracy well.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a fast ellipse detection method based on geometric constraints. Background technique [0002] Ellipse is an important class of image features and one of the most common geometric elements in natural and artificial scenes. From the perspective of computer vision applications, fast and efficient detection algorithms for elliptical objects in real-scene images provide powerful analytical tools for technologies such as tire detection and object segmentation in industrial applications. [0003] Hough Transform (Hough Transform) is one of the most classic ellipse detection algorithms, which uses a voting mechanism to fit ellipses. Since the clustering analysis needs to be performed in the five-dimensional parameter space, the algorithm will consume a lot of storage space and time when running. The improved algorithm of the Hough transform algorithm includes the Randomized Hou...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/46
CPCG06T7/0004G06T2207/20061G06V10/443G06V10/44
Inventor 贾棋樊鑫宋连博邱铁罗钟铉王倩
Owner DALIAN UNIV OF TECH
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