When you buy your favorite products get when greeted, is its appearance, which is by mold factory, assembly plant workers in intensive care produced some eye examination by the people, some by automation equipment inspection, did not miss any defect.
Nowadays, with the deepening of the emergence and development of computer technology, artificial intelligence, science and technology, and research, there has been surface defects based on machine vision inspection technology. Emergence of this technology, greatly improving the efficiency of production operations, to avoid the accuracy due to operating conditions, the subjective judgment affect the test results, to achieve better and more accurate detection of surface defects more quickly identify product defects surface imperfections .
Defect detection fabric are widely used in defect detection, surface quality detection, aviation and astronautics. The traditional method of rules flaws and the scene is relatively simple occasions, can work very well, but not obvious, shape and diverse, chaotic scene of occasions, is no longer applicable. In recent years, recognition algorithm based on the depth of learning more and more mature, many companies, such as speed inlay made Moses began to try to deep learning algorithms applied to industrial applications.
Belonging to a product surface defect detecting machine vision technology, computer vision is to simulate the function of human vision, the image acquisition and processing from the specific kind, calculates the final actual detection, control and application. Defect detection surface of the product is an important part of the machine vision inspection, the accuracy of detection will directly affect the merits of the quality of the final product. Due to the use of manual detection methods already can not meet the needs of modern production and manufacturing processes, and the use of machine vision inspection well overcome this, the surface defect detection system is widely used to promote the company factory production and manufacturing high-quality products the development of intelligent automation.
Intelligent machine vision inspection system
Surface defect detection system and deep learning computer vision algorithms, speed embedded wisdom made QuickEmbed improve the accuracy and efficiency of detection. There are several steps that require attention.
First, the surface texture of the image to be analyzed is collected by the image collection system;
second, collected over an image segmentation process step by step, so that the product can be like surface defects can be classified according to its unique characteristic region;
third, further analysis of the target region in the above classification scribe region, so that more accurate and precise range.
After the above three-step process, wherein the product surface defects can be further confirmed and regions, so basically a surface defect detection step is completed.
Automated detection flowchart
Improve user productivity using machine vision technology, making the production of more detailed, clearer division of labor, while reducing the company's labor costs, save money and achieve integrated development of machine intelligence
Machine vision inspection technology which classification?
(1) In general, machine vision technology in accordance with the detection function can be distinguished: positioning disadvantages detection, counting / loss detection, measurement scale.
(2) Machine vision inspection technique in accordance with which the support device can be divided into: off-line detection system and the detection system.
(3) in accordance with the difference between the detection skill, generally three-dimensional visual inspection skills, mottled detection skills, skills measuring scale, the OCR skills.
Machine vision inspection technique is to eliminate defects, ambiguous, debris or other goods recess shortcomings, the function and performance is critical to ensure that the goods. Therefore now widely used in major professional trade disadvantages detection, detection of scale. The vision system can be detected using a variety of merchandise items, pin detecting system of the electronic component drawbacks visually or offset measurement system visually distinguish the color or shape of syringe components to check for errors and installation.
You can also include a lot of machine vision technology-related applications, for example, identify license plates and traffic flow occupation of detection, drug detection professional packaging, beverage packaging professional capacity detection and detection, enlarging its detection tobacco profession and outside packaging, testing, installation detects the car occupations, professional print quality inspection, weld inspection professional textile cloth flaw detection, metal detection screws career, sorting goods transport profession, occupation fruit sorting food, electronics and career installation location, occupation steel plate appearance of the shortcomings detected, smart metering, smart metering, etc. are applied.