A Circular Detection Method Using Sparse Storage Structure
A storage structure and circular detection technology, applied in image data processing, instruments, calculations, etc., to achieve low space complexity, simplify the calculation process, and improve detection efficiency
Active Publication Date: 2015-11-25
XI AN JIAOTONG UNIV
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[0010] In order to solve the problems existing in the actual application of the existing circle detection method, the purpose of the present invention is to provide a circle detection method using a sparse storage structure, which can quickly, accurately and robustly detect the circular target object
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[0035] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
[0036] The present invention is a circular detection method using a sparse storage structure, figure 1 It is a flow chart of the method, including the following steps:
[0037] Step 1: Image preprocessing:
[0038] This step obtains the edge point object and its gradient direction for matching degree voting. Canny method is used for edge point detection, and 3x3Sobel convolution template is used for gradient direction calculation. In this way, the edge point set V={v is obtained from the original input image e =(xv e ,yv e )|e=1,...,E} and the corresponding gradient direction {f e |e=1,...,E}, E is the number of edge points.
[0039] Step 2: Discrete the circle to generate a set of voting directions, construct a sparse storage structure, and record the voting direction, voting position and voting value of edge points independe...
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The invention discloses a roundness detection method adopting a sparse storage structure. The method includes the steps that firstly, images are preprocessed; secondly, a disperse circumference generates a set of vote directions to construct the sparse storage structure, and vote directions, vote positions and vote values are recorded, wherein edge points of the vote directions, the vote positions and the vote values do not rely on a radius; thirdly, the sparse storage structure is retrieved, the vote positions of all the disperse vote directions are obtained, a given radius researching range is dispersed, a translation vector is generated according to the dispersed radius and the directions, the vote positions are horizontally moved, and a vote chart is generated by adding the vote values; fourthly, a circle center and the radius are analyzed according to the vote chart. The roundness detection method adopts the sparse storage structure, therefore, time and space complexity in the calculating process of voting can be effectively reduced, the detection process has instantaneity, and the method can meet actual application requirements due to the fact that the detection effect and the robustness of images in different scenes are both superior to those of other methods at present.
Description
technical field [0001] The invention belongs to the field of computer vision object detection, and in particular relates to a circular detection method using a sparse storage structure. Background technique [0002] As a common object in the visual world, circles frequently appear in our daily life, such as used coins, car tires, circular traffic signs, etc. Using computer vision technology, it is of great significance to recognize circular objects in the image. For example, when banks count the number of coins, they usually use manual counting, which is time-consuming and labor-intensive. In contrast, if the coins are photographed and detected The circular object in this image can achieve the purpose of coin counting, saving time and effort. Therefore, it is very necessary to provide an accurate and fast circle detection method. [0003] After decades of development, various methods have been proposed for circle detection at home and abroad. However, from the perspective ...
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IPC IPC(8): G06T7/00
Inventor 苏远歧刘跃虎黄骁爨伯男
Owner XI AN JIAOTONG UNIV