Machine vision-based automatic leather lineation method and apparatus

Abstract

A machine vision-based automatic leather lineation method is characterized in comprising the following steps: step S1, leather capturing: quickly capturing leather from a leather placing rack to a conveyor by using a manipulator; step S2: real-time scanning: performing, by a camera placed above the conveyor, real-time scanning on an image on the conveyor, and determining, by using an algorithm, whether the leather completely enters a view field of the camera; step S3: leather contour data extraction: after the leather completely enters the view field of the camera, analyzing an edge contour of the leather by using an image processing algorithm, and transforming the edge contour into an actual physical coordinate; step S4: lineation track determining: according to actual extracted contour data of the leather, searching a database for a template matching the data, and correspondingly determining a lineation track; and step S5: lineation: after determining the lineation track, performing leather lineation by using a Delta parallel robot. The Delta parallel robot is used to implement lineation, and the present invention has advantages of being high in accuracy and fast in speed.

Description

technical field [0001] The invention relates to a leather automatic scribing technology, in particular to a method and device for quickly realizing scribing by using a robot. Background technique [0002] Leather is widely used in clothing, bags and other fabrics. During the production of these items, depending on the style and size, it is necessary to cut the leather, or to mark lines (marks) on the leather for the convenience of subsequent operations, all of which require a precise track. Due to the diversity of leather shapes and the uncertainty of placement, the fixed trajectory is obviously difficult to meet the requirements of subsequent processes. However, manual operation has disadvantages such as low precision and slow speed, so its production efficiency and product quality are relatively low, which is not in line with the rapid development of the industry. At present, machine vision is widely used in the recognition and positioning of workpiece contours and other...

AI Technical Summary

Problems solved by technology

Due to the diversity of leather shapes and the uncertainty of placement, the fixed trajectory is obviously difficult to meet the requirements of subsequent processes

However, manual operation has shortcomings such as low precision and slow speed, so its production efficiency and product quality are relatively low, which does not conform to the rapid development of the industry.

Images