Intelligent recognition, counting, and detection algorithm for quasi-circle object facing packaging industry

Abstract

The invention discloses an intelligent recognition, counting, and detection algorithm for a quasi-circle object facing a packaging industry. According to images collected by an industrial camera, effective regions where quasi-circle objects are located are obtained. An image pretreatment method includes: removing original image noises by using a median filtering algorithm and obtaining binary images after image denoising by using an adaptive local binary algorithm. Geometric feature extraction is carried out by detection for four times; to be specific, quasi-circle objects with normal areas after binaryzation are detected for first detection; the rest of quasi-circle objects with defects are detected after first detection during the second detection process; quasi-circle objects at an uneven region are detected during the third detection process; and quasi-circle objects may existing at a detection boundary are detected during the fourth detection process. Therefore, the counting accuracy of quasi-circle three-dimensional objects is improved; and the packaging requirement is low and the detection robustness is high. Meanwhile, real-time, rapid, on-line monitoring can be realized. The algorithm is applied to detection of various quasi-circle objects.

Description

technical field [0001] The invention relates to a recognition technology detection algorithm, in particular to a packaging industry-oriented intelligent recognition counting detection algorithm for circle-like objects. Background technique [0002] Circle-like objects are ubiquitous in life, such as rods, wine bottles, medicine bottles, cigarette boxes, etc. Such circle-like objects inevitably need statistics in life. At present, manual direct counting or no detection is often used for counting boxed round objects. Using manual direct detection counting method is labor-intensive, eyes are prone to fatigue, counting accuracy is low, and the error varies from person to person. If the computer technology with fast capability and modern machine vision technology are used to detect circle-like objects, it can not only reduce subjective interference, improve recognition accuracy, but also reduce the heavy labor burden of workers, thereby improving work efficiency. [0003] In th...

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Problems solved by technology

[0004] Purpose of the invention: The purpose of the invention is to solve the problems of high labor intensity, low work efficiency, low accuracy and error-prone in the prior art, and provide a solution to the problem of expensive special industrial cameras and supporti

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