• Journal of IKEEE
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• v.18 no.2
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• pp.234-239
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• 2014

This paper proposes a new automatic detection method to inspect mura defects on display film surface using morphological image processing and labeling. This automatic detection method for mura defects on display films comprises 3 phases of preprocessing with morphological image processing, Gabor filtering, and labeling. Since distorted results could be obtained with the presence of non-uniform illumination, preprocessing step reduces illumination components using morphological image processing. In Gabor filtering, mura images are created with binary coded mura components using Gabor filters. Subsequently, labeling is a final phase of finding the mura defect area using the difference between large mura defects and values in the periphery. To evaluate the accuracy of the proposed detection method, detection rate was assessed by applying the method in 200 display film samples. As a result, the detection rate was high at about 95.5%. Moreover, the study was able to acquire reliable results using the Semu index for luminance mura in image quality inspection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.615-622
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• 2018

Recent advancements in camera communication (CamCom) technology using visible light exploited to use display as an luminance source to modulate the data for visible light data communication. The existing display-CamCom techniques uses the selected region of interest based camera capturing approach to detect and decode the 2D color coded data on display screen. This is not effective way to do communicate when the user on mobility. This paper propose the automatic display detection using Lambertian color segmentation combined with canny edge detection algorithms for CamCom in order to avoid manual region of interest selection to establish communication link between display and camera. The automatic display detection methods fails using conventional edge detection algorithms when content changes dynamically in displays. In order to solve this problem lambertian color segmentation combined with canny edge detection algorithms are proposed to detect display automatically. This research analysed different algorithms on display edge recognition and measured the performance on rendering dynamically changing content with color code on display. The display detection rate is achieved around 96% using this proposed solutions.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.77-80
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• 2022

Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. It has been populated because of the accuracy and consistency in terms of QC (Quality Control) of inspection processes. Also, it is important to predict the performance of an AVI to meet customer's specification in advance. AVI are usually suffered from false negative and positives. It can be overcome by providing extra information such as 3D depth information. Stereo vision processing has been popular for depth extraction of the 3D images from 2D images. However, stereo vision methods usually take long time to process. In this paper, retro optical system using reflectors is proposed and experimented to overcome the problem. The optical system extracts the depth without special SW processes. The vision sensor and optical components such as illumination and depth detecting module are integrated as a unit. The depth information can be extracted on real-time basis and utilized and can improve the performance of an AVI system.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.148-154
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• 2009

In recent days, large-sized flat-panel display (FPD) has been increasingly applied to computer monitors and TVs. Mura defects, appearing as low contrast or non-uniform brightness region, sometimes occur in manufacturing of the Thin-Film Transistor Liquid-Crystal Displays (TFT-LCD). Implementation of automatic Mura inspection methods is necessary for TFT-LCD production. Various existing Mura detection methods based on regression diagnostics, surface fitting and data transformation have been presented with good performance. This paper proposes an efficient Mura detection method that is based on a regression diagnostics using studentized residuals for automatic Mura inspection of FPD. The input image is estimated by a linear model and then the studentized residuals are calculated for filtering Mura regions. After image dilation, the proposed threshold is determined for detecting the non-uniform brightness region in TFT-LCD by means of monitoring the every pixel in the image. The experimental results obtained from several test images are used to illustrate the effectiveness and efficiency of the proposed method for Mura detection.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.15-20
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• 2007

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1295-1297
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• 2008

Large-sized flat-panel displays are widely used for PC monitors and TV displays. In this paper, frequency domain pre-filter algorithms are presented for detection of defects in large-sized Thin Film Transistor-Liquid Crystal Display(TFT-LCD) panel surfaces. Frequency analysis with 1-D, 2-D FFT methods for extract the periodic patterns of lattice structures in TFT-LCD is performed. To remove this patterns, frequency domain band-stop filters were used for eliminating specific frequency components. In order to acquire only defected images, 2-D inverse FFT methods to inverse transform of frequency domain images were used.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.11-15
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• 2020

In a typical initial setup of a PCB component inspection system, operators should manually input various information such as category, position, and inspection area for each component to be inspected, thus causing much inconvenience and longer setup time. Although there are many deep learning based object detectors, RetinaNet is regarded as one of best object detectors currently available. In this paper, a method using an extended RetinaNet is proposed that automatically detects its component category and position for each component mounted on PCBs from a high-resolution color input image. We extended the basic RetinaNet feature pyramid network by adding a feature pyramid layer having higher spatial resolution to the basic feature pyramid. It was demonstrated by experiments that the extended RetinaNet can detect successfully very small components that could be missed by the basic RetinaNet. Using the proposed method could enable automatic generation of inspection areas, thus considerably reducing the setup time of PCB component inspection systems.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.96-102
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• 2011

In this study, we performed algorithm development of automatic symptom degree for patient with hallux valgus one of the representative foot disease of morden. And this study proposes an efficient automated technique that is different from the original analog diagnosis for treatment and surgery of hallux valgus using digital image process. And we used X-Ray images of both a normal and a patient with hallux valgus in the procedure. First, we marked the standard angle on the X-Ray image of normal through Overlap & Add technique. Then we created a standard image through thinning filter and roberts filter(edge detection algorithm). Second, we used sobel filter of edge detection algorithm on the X-Ray image of patient. Moreover, we went another overlap & add technique procedure with both normal and patient image that we made. With the output, we projected the display detection image onto the screen. Finally, with the display detection image, we could measure and project the diagnosis angle of hallux valgus. And this confirms that this method is much more practical and applicable for another orthopedics disease than the prior one.

• Journal of the Semiconductor & Display Technology
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• v.7 no.3
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• pp.11-16
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• 2008

The authors investigated an overhead shuttle (OHS) system for automatic transferring the liquid crystal display (LCD) panels. The constructed tracks of OHS system include the linear and curve regions and have been installed on the ceiling to transfer the cassette of LCD glass along the closed-loop and open-loop tracks. In this study, the OHS system was implemented by a proposed linear motor to solve encoder installation and the system cost problems of the long distance transfer system. In addition, we utilized a new algorithm of the position detection and a new control algorithm for driving linear motor. The newly developed control algorithm was demonstrated from both a computer simulation and an experimentation, indicating that the highly reliable and speedy transfer system can enhance the LCD panel productivity of commercial OHS system.