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Intellectual image intelligent recognition and sorting device and recognition and sorting method

A technology of intelligent identification and sorting device, applied in the field of intelligent image intelligent identification and sorting, intelligent image intelligent identification and sorting device, which can solve the problems of misjudgment and less than 100% identification, and achieve simple operation and calculation. , The effect of fast and accurate identification and sorting, saving labor costs

Inactive Publication Date: 2016-04-20
温州裕宏电气有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The purpose of the present invention is to provide a kind of intelligent recognition and sorting device for intelligent images, which solves the problem that in the prior art, for the detection pieces that need to distinguish the front and back sides, the automation cannot be realized at low cost in the detection, identification and sorting links. In the field, especially in the process of high-speed automatic recognition of continuous movement of objects, there will always be misjudgments and missed judgments, and the problem of 100% recognition cannot be achieved

Method used

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  • Intellectual image intelligent recognition and sorting device and recognition and sorting method
  • Intellectual image intelligent recognition and sorting device and recognition and sorting method
  • Intellectual image intelligent recognition and sorting device and recognition and sorting method

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Embodiment 1

[0168] The method of the present invention is used for the identification that dynamic detection double gold has literal, and detection item and parameter are respectively: in original figure, utilize pixel size to be 752 * 480Pix; Literally through the dynamic detection and program, the edge of the boundary tracing and low grayscale connection image is obtained. In the boundary tracing and low grayscale connection mixture image, the standard deviation of the Gaussian filter is set to 3, and the maximum width of the detection edge is set to 11Pix; in the binarization diagram, the edge width is selected to be ≥ 3, and in the histogram, the detection method of the present invention is used to obtain the detection parameters of the double gold: the effective number of pixels is 56672Pix, the highest effective grayscale is 255Pix, and the lowest effective The grayscale is 94Pix; the high grayscale area SH is 42852Pix, the low grayscale area SL is 13820Pix, and the detection ratio K...

Embodiment 2

[0170] The method of the present invention is used for dynamic detection double gold no literal recognition detection, detection item and parameter are respectively: in original picture, utilize pixel size to be 752 * 480Pix; The frame rate is the CCD of MAX60F / S, to the double gold of continuous motion No Literal Through the dynamic detection and program, the edge of the boundary tracing and low grayscale connection image is obtained. In the boundary tracing and low grayscale connection mixture image, the standard deviation of the Gaussian filter is set to 3, and the maximum width of the detection edge is 7Pix ; In the binarized figure, the edge width selection ≥ 3, in the histogram, utilize the detection method of the present invention to obtain the detection parameters of double gold without literal: the effective pixel number is 56672Pix, the highest effective gray scale is 248Pix, the lowest effective gray The degree is 140Pix; the high gray area SH is 56464Pix, the low gr...

Embodiment 3

[0172] The method of the present invention is used for dynamic detection big white square silver dot reverse side recognition detection, and detection item and parameter are respectively: in original picture, utilize pixel size to be 752 * 480Pix; CCD of frame rate MAX60F / S, to continuous motion The back side of the big white square silver dot is dynamically detected and programmed to obtain the edge of the boundary tracing and low-gray-level mixed connection image. In the boundary-tracking and low-gray-level mixed connection image, the standard deviation of the Gaussian filter is set to 3, and the edge is detected. The maximum width is 8Pix; in the binary diagram, the edge width is selected to be ≥3, and in the histogram, the detection method of the present invention is used to obtain the detection parameters on the back of the silver point of the large white square: the number of effective pixels is 48825Pix, and the highest effective grayscale It is 240Pix, the minimum effec...

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Abstract

The invention discloses an intelligent-vision-based image intelligent recognizing-sorting device. The intelligent-vision-based image intelligent recognizing-sorting device is characterized in that at least one group of LED (Light Emitting Diode) lights is arranged above the position of a mobile path of a tested component; a CCD (Charge Coupled Device) camera connected with a PC (Personal Computer) is arranged above an axis of each of the LED lights; the PC is connected with a touch screen and a PLC (Programmable Logic Controller) controller; the output end of the PLC controller is respectively connected with corresponding blowing valves and (or) manipulators through a plurality of solenoid valves; and each of the blowing valves and (or) manipulators is arranged beside a transfer rack. The invention also discloses an intelligent-vision-based image intelligent recognizing-sorting method. The device and method realize recognizing and sorting in 100 percent, and also obviously improve the working efficiency and quality.

Description

technical field [0001] The invention belongs to the technical field of intelligent identification and detection, and relates to an intelligent identification and sorting device for intelligent images, and also relates to an intelligent identification and sorting method for intelligent images. Background technique [0002] Machine vision technology has non-contact, real-time, high speed, high precision, strong anti-interference, can greatly reduce costs, improve production speed and efficiency, and has broad application prospects in industrial quality inspection and control production. However, the existing machine vision detection and recognition basically has a better effect under static conditions. In many cases, the detection effect cannot reach zero false positives and zero missed detections, including the following aspects: [0003] 1. The methods to realize the detection of moving objects mainly include: 1) Background difference method: it can completely and quickly se...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B07C5/342B07C5/36
Inventor 黄和平黄一淼
Owner 温州裕宏电气有限公司