Daehwa Jeong

Defect classification for the inspection of TFT LCD glass

Serious pattern defects and particles co-exist on the glass and only a few defects can cause serious quality problem. Now, if there would be a way to classify the defect by its potential lethality, it would be useful to control the product quality and loss of review time. This paper presents a method to classify the defect by using reviewing images. First, several defect types were investigated to develop an algorithm. In next, efficiency of the algorithm was verified in a plant. The result was good enough to utilize the information of classified defect type. Finally, the algorithm was applied to remove the information of trivial defects. The result was good to increase a throughput of whole process under little risk.

Defect Classification Using Bayesian Approach for Tape Substrate Inspection System

Abstract The inspection of ultra-fine pitch patterned tape substrate (TS) requires high resolution optics. In the process of picking out defects at the level of the critical dimension through image processing, however, trivial blemishes formed by dust or micro particles may be detected simultaneously. This leads to unnecessary work on the part of operators reviewing and verifying the additional detected points. To maximize the efficiency of the inspection process, we need to identify and classify the defect candidates whether it is a real pattern defect or simply a trivial blemish by dust. In this article, we propose a Bayesian approach to classify the defective images based on the measures of the image features. The features of the defective region in terms of shape and brightness are obtained from a series of proper image analysis with FFT. Based on the data collected from experiments, we devised a statistic model for classification.

Zone-Based Inspection and Defect Classification for LCD Manufacturing: Trivial Defect Free Procedure for TFT Glass Inspection

Inspection of thin film transistor (TFT)-patterned glass is one of the important processes for TFT-LCD panel manufacturing. Minute pattern defects and particles coexist on the glass and a few defects can cause serious quality problems. If there was a way to classify the defects by its potential fatality, it would be useful to control the product quality and loss of inspection time. This article introduces a rule-based approach of zone-based inspection and defect classification. For the zone-based processing, a defect classifier and its decision boundary were also proposed to differentiate non-fatal defects. An experimental result showed that the defect classifier was useful to select non-fatal defects and over 70% of the trivial defects could be selected with little risk of quality problems. This article also presents an application result to utilize the method in a plant. Since prejudged trivial defects have little influence on panel quality, they could be eliminated without interfering with the factor effecting overall final quality. This enables to save post-inspection time. The application results are sufficiently promising to save over 30% in inspection time and, furthermore, only 0.02% of fatal defects are not detectable. The proposed method also brings about an additional return of yield improvement because operator-error is found to be decreased as the defect candidates decrease because of the application of the proposed method.

Study on an inspection method of repeated pattern

LCD(Liquid Crystal Display) became one of the most popular display devices in these days. The TFT(Thin Film Transistor) substrate is the key part of active matrix LCD. TFT is an electrical device to activate a displaying cell. To display an image precisely, several millions of identical transistors are patterned on a wide glass panel. Since a minute damage on the pattern can causes a serious defect to display, it is important to inspect the pattern precisely. Taking the advantage of the fact that the pattern of good cell should be identical to that of adjacent cells, it would be a convenient way to compare a cell with its neighbor cells to find a defect. In practical applications, if the period of repetition could be represented as an integer number of digitized image pixel, it would be possible to find a damaged pixel readily. However, the period of pattern depends on the product size and cannot be determined as an integer always. In this paper, so called, pseudo-matching magnification algorithm has been introduced to solve the problem. A digital image was magnified and period of pattern can be determined as an integer from the processed image. It has been shown that the defects could be enhanced after the preprocessing of digital image. As a result, a TFT-pattern inspection system has been developed and it has been shown the proposed method is compatible for the inspection of repeated pattern.

A Reflectometry Approach for Rippling Defect Measurement on High Glossy Surface

Locally deformed defects, rippling, on home appliances cause appearance quality issues, and they look enlarged on high glossy surface. The defects need to be detected in the production line, where the product is moving on a conveyor transfer system. Inspection is executed by an expert but it is very subjective and not quantitative so that even quality assurance team cannot manage the defects levels. As a solution, a visual measurement methodology based on one shot reflection Moire is developed to obtain numerical data about surface defects. The system is introduced in this article, and experiment results are shown.

The Novel Approach for Multi-layered Thin Film Inspection Based on 3D Surface Reconstruction

Currently, thin films are widely used for the display product. Furthermore, the protective film is often attached to touch films and cover glasses for their safety. However, relatively few researches have been done for those products and there are many issues when we use current inspection system for multi-layered thin films. In this paper, we propose the novel method to inspect them based on 3d surface reconstruction. We use line profiles of each layer which composes the multi-layered thin film. Also an enhanced light source system is applied to inspect user specified layers by using the patterned retarder. Also we propose the robust defect analysis system by using user specified depth images. We made 3d inspection platform which shows very stable results regarding defects detection among layers. Finally, our study is applied to the commercial system which is used for visual inspection of the film.

Phase Map Generation for Phase Shift Moire Using CUDA

Phase shift Moiré is a very popular and one of the most successful techniques for shape measurement of 3-D objects such as PCB (printed circuit board), TFT (thin film transistor), LCD (Liquid crystal display) etc. Various implementations of phase shift moiré are available for improving accuracy and/or speed. Although, these methods contribute a lot in reducing the computation with some compromise in accuracy, there is a lot of scope of improving the performance of these algorithms with increased accuracy, especially when specialized hardware like GPU is available. GPU contains many core or processing elements that can process the same work concurrently resulting in dramatic increase in performance. In this paper, we propose the parallel implementation of the phase shift moiré method on CUDA. A novel method called image stacking method is proposed that can also be used for CUDA implementation of similar algorithms to improve performance. Using this technique, we are able to execute the application 180 times faster compared to the CPU implementation.

A patterned illumination and phase integration imaging method for high-glossy surface evaluation

Visual and optical measurement and evaluation technologies are highly required in quality control of painting and final coating process. We propose a novel approach to evaluate the appearance quality of high glossy surface object. To image the surface roughness, by which the object looks like orange peel, we employ a patterned illumination with phase shifting. The object can be exposed to various illumination conditions according to the phase of pattern lighting. By ac hieving a series of images and analyzing the phase, an image can be synthesized as specific phase selectively. The grade of su rface quality in terms of orange peel is then evaluated based on a specific phase. We have conducted evaluation tests on sample pr oducts, which show the usability of the proposed method.

Development of a Fast and High Resolution X-Ray Imaging Sensor for In-Line Inspection of Tape Substrate

In an automated tape substrate inspections, machine vision is widely adopted for high throughput and cost advantages. However, conventional methods are overly sensitive to foreign particles or have limitations in detecting three-dimensional defects such as top over-etched defect. Foreign particles such as dustsdo not affect the integrity of the final product and are often detected as defects during inspection. To complement vision inspection systems, a prototype fast and fine spatial resolution X-ray imaging sensor has been developed. This image sensor, based on an optoelectronic device – the microchannel plate (MCP), has a spatial resolution of 20 μm and functions at frame rate of 30 fps. X-ray imaging is appropriate as it is virtually transparent to dust particles and provides information regarding the thickness of the copper wire patterns.

A novel line detection method using magnetic sensor for the optical inspection of electrical short defects on TFT LCD

A novel detection method is suggested using magnetic sensor to detect the short-defect line on LCD-TFT panel. With the voltage applied to the TFT panel, current flows along the short-defect line generating magnetic field around it. By scanning the magnetic sensor across the TFT panel, the defect line can be detected. Vision inspection is performed along the detected line to find out the defect point. Three main types of short-defects on TFT panel are tested and their locations are successfully detected by the suggested method.