Display Panel Industry

Detecting Appearance Defects

Scratches, dents, etc.
Detecting Dimensional Defects

Inconsistencies in size, excessive deviations, etc.
Detecting Functional Defects

Battery life, wireless connectivity, etc.
Detecting Safety Performance Defects

Battery overheating, electrical short circuits, etc.

Industry Pain Points

Currently, as panel sizes increase, resolutions rise, the number of pixels increases, and individual pixels become smaller, the wiring between lines becomes very dense, greatly increasing the difficulty of film manufacturing. During the panel manufacturing process, a large number of short circuits between the gate lines and common electrode lines inside the panel cause an increase in defect rates. Machine vision inspection can quickly detect defective positions on display panels and how to timely intercept panels with short circuits and micro-short circuits, preventing them from moving to the backend assembly process, which is a key factor in improving the efficiency of display panel detection.

Solutions

Flexible circuit boards
LCD screens

FPC Flexible Circuit Board Defect Detection

Flexible circuit boards have developed rapidly in recent years. The variety of FPC board types and the miniaturization of products mean that traditional manual inspection can no longer meet the development needs of FPC boards. Machine vision-based detection methods provide a way to solve the automation detection of FPC boards.
his project analyzed the current research status of machine vision detection systems at home and abroad, improved some algorithms applied to FPC flexible circuit board defect detection, and proposed detection algorithms based on global and local defects, which have been verified to meet the requirements of online detection.

Strong compatibility, well-balanced detection speed and accuracy
Reasonable use of image segmentation, edge feature extraction, mathematical morphology, and other image processing and analysis techniques
High resolution, effectively solved
the problem of insufficient CCD resolution

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LCD Screen Measurement

With the rapid development of image processing and pattern recognition technology, the level of intelligence and automation in industrial production is gradually deepening. Although the field of production automation is already quite extensive, manual inspection is still required for defect detection of products, such as surface scratches, spots, pits, and other appearance features. This inspection method not only increases inspection costs but also involves issues caused by human subjective factors, such as misjudgment, missed detection, low inspection accuracy, and lack of standardization. This project studied theoretical algorithms applied to LCD screen defect detection, including camera calibration and image correction, pattern matching, and considered two types of distortion to simplify the template to improve image distortion, comprehensively developing and implementing technology for an LCD screen defect detection system.

Balanced performance:
Well-balanced detection speed and accuracy
Image processing:
Reasonable use of image segmentation, edge feature extraction, mathematical morphology, and other image processing and analysis techniques
High resolution:
Effectively solved the problem of insufficient CCD resolution