• Journal of KIISE:Software and Applications
• /
• v.34 no.5
• /
• pp.447-454
• /
• 2007

TFT-LCD(Thin Film transistor liquid crystal display) has become actively used front panel display technology with increasing market. Intrinsically there is region of non uniformity with low contrast that to human eye is perceived as defect. As the gray level difference between the defect and the background is hardly distinguishable, conventional thresholding and edge detection techniques cannot be applied to detect the defect. Between the patterned and un-patterned LCD defects, this paper deals with un-patterned LCD defects by using independent component analysis, adaptive thresholding and skewness. Our method showed strong results even on noised LCD images and worked successfully on the manufacturing line.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.6
• /
• pp.852-859
• /
• 2009

Normally, to extract the defect in TFT-LCD inspection system, the image is obtained by using line scan camera or area scan camera which is achieved by CCD or CMOS sensor. Because of the limited dynamic range of CCD or CMOS sensor as well as the effect of the illumination, these images are frequently degraded and the important features are hard to decern by a human viewer. In order to overcome this problem, the feature vectors in the image are obtained by using the average intensity difference between defect and background based on the weber's law and the standard deviation of the background region. The defect detection method uses non-linear SVM (Supports Vector Machine) method using the extracted feature vectors. The experiment results show that the proposed method yields better performance of defect classification methods over conveniently method.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.5
• /
• pp.45-54
• /
• 2009

In this paper, we propose an adult images detection algorithm using a mean intensity filter and an improved 2D Hough Transform. This paper is composed of three major steps including a training step, a recognition step, and a verification step. The training step generates a mean nipple variance filter that will be used for detecting nipple candidate regions in the recognition step. To make the mean variance filter, we converts an input color image into a gray scale image and normalize it, and make an average intensity filter for nipple areas. The recognition step first extracts edge images and finds connected components, and decides nipple candidate regions by considering the ratio of width and height of a connected component. It then decides final nipple candidates by calculating the similarity between the learned nipple average intensity filter and the nipple candidate areas. Also, it detects breast lines of an input image through the improved 2D Hough transform. The verification step detects breast areas and identifies adult images by considering the relations between nipple candidate regions and locations of breast lines.

• Journal of the Korean Magnetics Society
• /
• v.16 no.6
• /
• pp.305-308
• /
• 2006

Magnetic flux leakage (MFL) pigs are traditionally used for the detection of gross corrosion on steel pipelines used for the transmission of natural gas. Alternative nondestructive evaluation (NDE) modalities are required for the detection of stress corrosion cracking (SCC) which tends to exist in colonies oriented axially along the length of the pipeline. This paper describes the use of multiphase rotating magnetic fields in the remote region of the probe as a possible SCC detection mechanism. Details of a prototype pig and test rig are given and the challenges associated with the finite element modeling of the device are discussed. Initial experimental results show that this novel NDE modality is sensitive to axially oriented tight cracks.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.4
• /
• pp.1278-1284
• /
• 2010

In this paper, we propose a new mura detection algorithm for TFT-LCD effectively, which is based on multi-point, 2-dimensional FFT. Since mura in TFT-LCD has a certain area shape, it is seen as a sin wave in a LCD line. Since shapes of mura can be seen a circle, horizontal oval, or vertical oval, it is shown that they can be detected by 2-dimensional FFT easily. Through simulation for test image, it is shown that proposed algorithm can detect various sizes of mura. The proposed algorithm can be utilized in automatic test equipment for effective TFT-LCD mura detection.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.12
• /
• pp.7302-7308
• /
• 2014

Detecting target objects robustly in natural environments is a difficult problem in the computer vision and image processing areas. This paper suggests a method of robustly detecting target objects in the environments where reflection exists. The suggested algorithm first captures scenes with a stereo camera and extracts the line and corner features representing the target objects. This method then eliminates the reflected features among the extracted ones using a homographic transform. Subsequently, the method robustly detects the target objects by clustering only real features. The experimental results showed that the suggested algorithm effectively detects the target objects in reflection environments rather than existing algorithms.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.5
• /
• pp.224-230
• /
• 2013

Lane boundary detection plays a key role in the driver assistance system. This study proposes a robust method for detecting lane boundary in severe environment. First, a horizontal line detects form the original image using improved Vertical Mean Distribution Method (iVMD) and the sub-region image which is under the horizontal line, is determined. Second, we extract the lane marking from the sub-region image using Canny edge detector. Finally, K-means clustering algorithm classifi left and right lane cluster under variant illumination, cracked road, complex lane marking and passing traffic. Experimental results show that the proposed method satisfie the real-time and efficient requirement of the intelligent transportation system.

• Journal of Korea Multimedia Society
• /
• v.13 no.11
• /
• pp.1610-1620
• /
• 2010

This paper proposes a motion-adaptive 3-D deinterlacing algorithm based on an adaptive-thresholded motion detection and an interpolation method using binary patterns to compensate motion missing and false motion errors. For efficient motion detection, we adaptively decided a threshold value according to the complexity of image. Many edge-based interpolation algorithms have been proposed to improve the subjective quality. Recently, to efficiently interpolate low angle edge and line, a method using predefined binary patterns has been proposed. In this paper, we propose an improved method by modifying the binary patterns. Simulation results have shown that the proposed method provides better performance than the existing methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.1
• /
• pp.1-11
• /
• 2021

This paper presents a procedure to extract lane line models using a set of proposed methods. Firstly, an image warping method based on homography is proposed to transform a target image into an image which is efficient to find lane pixels within a certain region in the image. Secondly, a method to use the combination of the results of edge detection and HSL (Hue, Saturation, and Lightness) transform is proposed to detect lane candidate pixels with reliability. Thirdly, erroneous candidate lane pixels are eliminated using a selection area method. Fourthly, a method to fit lane pixels to quadratic polynomials is proposed. In order to test the validity of the proposed procedure, a set of black-box images captured under varying illumination and noise conditions were used. The experimental results show that the proposed procedure could overcome the problems of color-only and edge-only based methods and extract lane pixels and model the lane line geometry effectively within less than 0.6 seconds per frame under a low-cost computing environment.

• Proceedings of KOSOMES biannual meeting
• /
• 2005.11a
• /
• pp.203-208
• /
• 2005

The CGO (Chip on Glass) to be measured a few micro unit is captured by line scan camera for the accuracy of chip inspection. But it is very sensitive to scan speed and lighting conditions. In this paper, we propose the methods to increase the accuracy of faulty detection by image subtraction. Image subtraction is detected faultiness by subtracting the image of a ' perfect ' COG from trot of the sample under tests. For image subtraction to be successful, the two images must be pre챠sely registered The two images is registered by the area segmentation pattern matching, and the result image get by operating the gradient mask image and the image to practice subtraction. A series of experimentation showed that the proposed algorithm shows substantial improvement over the other image subtraction methods.