Kyung-Moo Huh

A viewpoint-dependent autostereoscopic 3D display method

Among the several types of 3D display method, the autostereoscopic method has an advantage that one can enjoy 3D images without any additional device, but the method has a disadvantage of a narrow viewing zone and so the moving viewer cannot see the 3D image continuously. This disadvantage can be overcome with the detection of viewers positional movement by head tracking. In this paper, the authors suggest a method of detecting the two eyes position of a moving viewer by using images obtained through a color CCD camera. The suggested method consists of the preprocessing process and the eye-detection process, and through the similarity measurement of stereo image rendered at z-buffer by Open Inventor and captured by stereo camera using robot, one could find that viewpoint-dependent 3D images obtained by their proposed method is optimal to the viewer.

Robust and consistent defect size measuring method in Automated Vision Inspection system

Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on same defect with some variations on position or rotation mainly because we get different image. It is caused by possible variations from image acquisition process including optical factors, non-uniform illumination, random noises, and so on. For this reason, conventional area based defect measuring method has a problem on robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem. We utilize volume information which is completely ignored in the area based defect measuring method. We choose a cylinder shape as a defect model for experiment. The results show that our proposed method dramatically improves robustness and consistency of defect size measurement. Given proper modeling, the proposed volume based measuring method can be applied to various types of defect.

An approach of the order identification for the transfer function of systems with superimposed noise

Conventional methods for estimating the transfer function models based on deterministic perturbations of the input such as step, pulse and sinusoidal changes have not always been successful because the response of the system may be masked by uncontrollable disturbances, collectively referred to as noise. Particularly in multisensor-integrated systems, the effect of noise from the sensors is not negligible and so the information on the system model and noise model is important for the accurate control of the integrated systems. In this paper, a statistical method for estimating the transfer function models with superimposed noise is presented. Similarity between the auto-correlation function of linear filter system driven by white noise and the impulse response function of dynamic system enables us to develop a method of identifying the order of dynamic systems. In order to identify the systems with superimposed noise, this paper derives R-, S-, and GPAC array which provide us with pretty clear information on the identification of dynamic systems with noise. From the derived arrays, we can obtain the order of transfer function model and also the order of noise model represented by an ARMA process. Finally, an example of order identification of transfer function model and noise model is presented to show effectiveness of the proposed algorithm.

An Improved Histogram Specification using Multiresolution in the Spatial Domain for Image Enhancement

The histogram specification turns a shape of a histogram into that we want to specify. This technique can be applied usefully in various image processing fields such as machine vision. However, the histogram specification technique has its basic limits. For instance, the histogram does not have location information of pixels. Also, the accuracy of specification drops because of quantization error of digitized image. In this paper, we proposed a multiresolution histogram specification method in order to improve the accuracy of specification in terms of resemblance between destination and source image. The experimental results show that the proposed method dramatically enhances the accuracy of specification compared to the conventional methods.

An Enhanced Histogram Matching Method for Automatic Visual Defect Inspection robust to Illumination and Resolution

Machine vision inspection systems have replaced human inspectors in defect inspection fields for several decades. However, the inspection results of machine vision are often affected by small changes of illumination. When small changes of illumination appear in image histograms, the influence of illumination can be decreased by transformation of the histogram. In this paper, we propose an enhanced histogram matching algorithm which corrects distorted histograms by variations of illumination. We use the resolution resizing method for an optimal matching of input and reference histograms and reduction of quantization errors from the digitizing process. The proposed algorithm aims not only for improvement of the accuracy of defect detection, but also robustness against variations of illumination in machine vision inspection. The experimental results show that the proposed method maintains uniform inspection error rates under dramatic illumination changes whereas the conventional inspection method reveals inconsistent inspection results in the same illumination conditions.

Defect Detection Method using Human Visual System and MMTF

Abstract: AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. Defect detection is not an easy process because of noises from various sources and optical distortion. In this paper the acquired images from a TFT panel are enhanced with the adoption of an HVS (Human Visual System). A human visual system is more sensitive on the defect area than the illumination components because it has greater sensitivity to variations of intensity. In this paper we modified an MTF (Modulation Transfer Function) in the Wavelet domain and utilized the characteristics of an HVS. The proposed algorithm flattens the inner illumination components while preserving the defect information intact. Keywords: automatic inspection, defect, detection, modulated transfer function, HVS I. 서론 머신 비전 기술은 영상을 기반으로 하는 자동결함 검사시스템 분야에서 생산성 향상과 품질 관리 자동화에 기여해 왔다[1]. 일반적으로 시각적 검사와 품질 제어는 전문적인 목시 검사자들에 의해 수행되어 왔다. 하지만 목시 검사자는 검사가 정확한 반면에 쉽게 지치고 검사 속도가 느리며 당일의 기분과 컨디션에 따라 검사 품질에 일관성이 떨어 질 수 있으며 인건비가 들어가므로 비용이 많이 든다. 이러한 점을 개선하기 위해 자동 결함 검사 시스템(automatic vision inspection system)이 도입되었다. 이 시스템은 인간의 시각 및 인지 시스템을 모방하여 비전 센서(camera)를 탑재하여 실시간으로 영상을 획득하여 영상 분석을 통해 결함을 자동으로 탐지하여 그 위치나 크기, 모양 혹은 배경과의 명암차 등 그 결함에 대한 정보를 추출하고 자동으로 보고하는 시스템이다. 최근 수 십 년 동안 자동결함 검사시스템은 그 활용도가 뛰어나 많은 응용 분야에서 활발히 연구가 되어 왔다[2]. 특히 영상 처리 및 분석과 프로세서의 기술이 발전함에 따라 신속 정확한 검사가 가능하게 되었다. 특히 영상 처리 및 분석 여기서기술은 검사 성능을 좌우하는 매우 중요한 기술로서 다양한 결함 추출 알고리듬이 개발되어 왔다[3,4,7,8,9]. 하지만 영상 획득 과정에서의 다양한 원인의 잡음과 광학적 왜곡으로 인해 Field에서 요구하는 신뢰성 있는 결함 검출은 그리 쉬운 문제가 아니다. 본 연구에서는 TFT-LCD 표면 영상에 대하여 실제 인간 시각이 인지하는 특성을 반영한 영상 개선을 수행하였다. 인간 시각은 TFT-LCD 표면 영상의 내부 조명성분 보다는 결함 정보에 더 민감하게 반응하는데, 이는 인간 시각이 고주파 상에서 일어나는 변화보다 TFT-LCD 영상 내 휘도 흐름 (불균일도)과 같은 저주파 상에서의 휘도 변화에 대한 감지력이 더 뛰어나기 때문이다. 이에 본 연구에서는 이러한 인간 시각의 특성을 함수화 한 MTF (Modulation Transfer Function)를 웨이브렛 도메인에 적합하게 수정하고, 이를 통해 내부 조명을 평탄하게 모델링하면서 결함정보는 보존하는 알고리즘을 설계하였다. II 장에서는 수정된 MTF (Modulation Transfer Function) 에 대해서 설명하고 III 장에서는 HVS (Human Visual System, 인간지각시스템)에 대해 간단히 설명한다. IV 장에서는 MMTF와 HVS를 이용한 결함 추출 방법에 대해 설명하고 V 장에서는 실험 결과를 분석하였다. 마지막으로 VI 장에서 결론을 맺는다. II. MODIFIED MODULATION TRANSFER FUNCTION 식 (1)은 주파수 f 에 대한 MTF의 특성을 수식화 한 것이다. Hf f f

Statistical Prediction of False Alarm Rates in Automatic Vision Inspection System

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. It is important to predict the performance of an AVI to meet customer`s specification in advance. Also the prediction can indicate the level of current performance of an AVI system. In this paper, we propose a statistical method for prediction of false alarm rate regarding inconsistency of defect size measurement process. For this purpose, only simple experiments are needed to measure the defect sizes for certain number of times. The statistical features from the experiment are utilized in the prediction process. Therefore, the proposed method is swift and easy to implement and use. The experiment shows a close prediction compared to manual inspection results.

Automatic Visual Inspection System of Remocon using Camera

The visual inspection method that depends on human`s eyes has some problem that a lot of variations happen in examination according to bodily, spiritual state of the checker. We automate remocon inspection process using CCD camera. Our developed inspection system can be used in any remocon production line without the user`s big handling. Our inspection system was developed using PC, CCD Camera, Visual C++ for universal work place. The accuracy of proposed system was improved about 3.2[%] than the conventional pattern matching method and the processing time was decreased about 119[ms]. Also we showed that our inspection system is more robust to lighting circumstances.

The method of movement-velocity calculation of viewer by using two eyes image for 3D display for multiple viewers

We calculate the moving velocity of a viewer by using two eye images obtained at different times through the camera. This process is necessary for the future 3D display technique, in which a moving viewer can see a 3D image continuously. We first extract two eyes image and calculate the pixel coordinate of the center point between the two eyes. Next, we calculate the moving velocity in two dimension by comparing the two center point coordinates obtained at different times.

The two eyes position detection algorithm for a moving viewer using color camera image

In this paper, we suggest methods of detecting the two-eyes position of moving viewer by using images obtained through the color CCD camera. This procedure is necessary for future 3D display technique, in which the moving viewer can see the 3D image continuously. We develop two algorithms for detecting the position of two eyes: one is the method of using this mask block and the other is that of using pixel analysis.