• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.406-414
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• 1997

A real-time inspection system is developed using line scan cameras. Several improved algorithms are proposed for real-time detection of defects in this automated inspection system. The major improved algorithms include the preprocessing, the threshold decision, and the clustering algorithms. The preprocessing algorithms are for exact binarization and the threshold decision algorithm is for fast detection of defects in 1-D binary images. The clustering algorithm is also developed for fast classifying of the defects. The system is applied to PCBs(Printed Circuit Boards) inspection. The typical defects in PCBs are pits, dent, wrinkle, scratch, and black spots. The results show that most defects are detected and classified successfully.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1667-1670
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• 2014

This paper describes a method for detecting the pupil region and identification of the eye status for driver drowsiness detection system. This program detects a driver's face and eyes using viola-jones face detection algorithm and extracts the pupil area by utilizing mean values of each row and column on the eye area. The proposed method uses binary images and the number of black pixels to identify the eye status. Experimental results showed that the accuracy of classification eye status(open/close) was above 90%.

• The Journal of the Korea Contents Association
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• v.2 no.3
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• pp.80-86
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• 2002

In this paper, we propose the new optical security technique using two phase holograms based on interferometer. The encoded random phase image does not have any information on the original image. Without Hewing the key mask, one cannot decode the encrypted image and regenerate the original image. And the use of two phase only images in the proposed security system leads to maximum optical efficiency (100% in theory). Also they cannot be detected by an intensity detector such as a CCD camera. Computer simulations and optical experiments show performance of the proposed methods.

• Journal of Biomedical Engineering Research
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• v.5 no.1
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• pp.69-76
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• 1984

An automatic white blood cell differential counting system was developed, which consists of feature extractor, main control computer, auto focus and search part and data acquisition part. This system is used as a clinical instrument whose purpose is to classify white blood cell images. It may also be used for other binary image processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2862-2878
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• 2020

Data Security is the most challenging area in Internet communication, where most of the secret sharing schemes are proposed for binary images. But still it lacks in providing security for data communication, especially in image transmission. Traditional visual cryptography scheme generate meaningless diwies and the reconstruction phase leads to quality degradation over the secret image. In this work, an intelligent two dimensional secret share construction scheme is proposed. A secret image is expanded into n diwies with the choice of scheme selection. By Stacking all the qualified diwies to revert the secret image without content loss and less than s^* - 1 shares could not reveal any information about the secret image. The experimental results emphasize that the proposed secret share scheme is highly secured for image transmission.

• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.410-413
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• 1988

In this paper, the real-time optical associative memory using multiple hologram which is generated with two angular multiplexed reference beams and Fourier transformed object beam in the $BaTiO_{3}$ crystal based on DFWM mechanism. When one image is recorded in the $BaTiO_{3}$ crystal, complete image can be recalled by 9 % partial input of the stored original image without any additional thresholding and optical feedback process. As an experimental result of multiple Fourier hologram which is recorded with two binary images, OHCHAS and PARKHK, we can obtain complete image recalled by 1/6 partial input of the stored image.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.1
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• pp.137-142
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• 1990

A theory for the synthesis of a SDF including the filter modulation is suggested. In the filter synthesis, the iteration equation was used to iterate trial solution vectors. A computer simulation of the fSDF method using threshold binary images of the flight objects over a range of aspect angles was performed for POF and BPOF. The constructed fSDF filters are capable of obtaining the specified peak correlation response within a 1.7%-4.0% error range, after several iterations. However, the conventional pSDF/POFs, BPOFs are not. The results indicate POFs and BPOs can be made to perform well for distortion invariant optical pattern recognition using the fSDF method.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.50-53
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• 2000

It is effectively removed noise in the image using FCNN(Fuzzy Cellular Neural Network) applying fuzzy theory to CNN(Cellular Neural Network) structure and HD(Hausdorff Distance) commonly used measures for object matching. HD calculates the distance between two point set of pixels in two-dimensional binary images without establishing correspondence. Also, this method is proposed in order to improve the operation speed. In this paper, $\alpha$-LTSHD(Least Trimmed Square HD) operator applying $\alpha$-Trimmed to LTSHD, one field of HD, is applied to FCNN structure, and it is proposed as the modified method in order to remove noise in the image. Also, it is made a comparison with the other filters by using MSE and SNR after removing noise using the FCNNS which are applied $\alpha$-LTSHD operator through the computer simulation. In a result, FCNN performance which is applied the proposed $\alpha$-LTSHD demonstrated the superiority to the other filters in the noise removal.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.59-66
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• 1993

Stereo vision is useful in obtaining three dimensional depth information from two images taken from different view points. Neural network modeling for stereo matching, the key step in stereo vision, is defined by an energy function satisfying with three constraints proposed by Marr and Poggio. Stereo matching is then carried out through the network to find minimum energy corresponding to the optimized solution of the problem. An algorithm for stereo matching using an analog neural network is presented here. The network can reduce errors in initial state an early iteration steps by adoption of continuous sigmoid function in stead of binary state. The experimental results show good matching performance for sparse random dot stereogram and real image.