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Defect detection algorithm based on fast positioning

A defect detection and algorithm technology, applied in the direction of optical defect/defect, calculation, measurement device, etc., can solve problems affecting work efficiency and achieve the effect of simplifying complexity

Active Publication Date: 2020-12-01
BEIJING FOCUSIGHT TECH +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Obviously, this not only requires the operator to be cautious and careful, but also requires the operator to have a certain knowledge reserve in image processing, which also greatly affects the work efficiency

Method used

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  • Defect detection algorithm based on fast positioning
  • Defect detection algorithm based on fast positioning

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Embodiment Construction

[0031] The present invention will now be described in further detail in conjunction with the accompanying drawings and preferred embodiments. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0032] A defect detection algorithm based on fast positioning, the algorithm flow is as follows figure 1 shown, including the following steps:

[0033] 1. Perform initialization settings;

[0034] 2. Read the product image information. In this embodiment, the drug outer packaging box is taken as an example, hereinafter referred to as the drug package, and all the drug packages are the same printing batch; there are multiple detection objects on the drug package, such as barcodes and production marks , drug information, etc.; all detection objects on the drug package are classified into a large group, and ROI segmentation p...

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Abstract

The invention relates to a defect detection algorithm based on rapid positioning, including: 1) performing initialization settings; 2) reading product image information, taking objects with the same printing batch as a group, and performing segmentation processing on each object in the group ;3) Cluster the objects in the group to subdivide the group to obtain the refined group; 4) Search and filter the positioning core for each refined group; 5) According to the positioning information of the positioning core Perform affine transformation on the detection image according to different subdivided groups to obtain the correction image; use the detection parameter adaptive method to adjust and confirm the detection parameters; 6) product detection and output the detection result. The present invention not only does not need manual drawing of positioning kernels, but also does not require multiple learning images. Only one print image is needed to establish a quality standard template, which not only eliminates manual picking (selection of learning samples) but also simplifies the complexity of user operations ( Locating the drawing of the nucleus, learning the operation process).

Description

technical field [0001] The invention relates to the technical field of visual image detection, in particular to a defect detection algorithm based on fast positioning. Background technique [0002] With the continuous advancement of printing technology, the printing industry is gradually developing towards high speed and high quality. Non-contact detection based on machine vision has become the main method for online detection of printed product defects. At present, the traditional machine vision inspection method uses the template image as the standard, and judges whether the real-time product is defective through the template matching method. [0003] However, due to the instability of the paper feed, the instability of the imaging system, and the relative position deviation of the printed image on the standard printed matter and the printed matter to be inspected, it is usually necessary to manually select the positioning kernel during product modeling, and then before pr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/11G06K9/62G01N21/88
CPCG06T7/0004G06T7/11G01N21/8851G06T2207/10004G06T2207/20104G06T2207/20164G06T2207/30144G01N2021/8887G06F18/23
Inventor 都卫东王岩松和江镇吴健雄张铃华
Owner BEIJING FOCUSIGHT TECH
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