• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.297-300
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• 1999

중요한 정보 암호화하여 복수 회원에게 분산시킨 후 회원의 합의에 의하여 해독이 가능하게 하는 thresholding scheme은 visual cryptography에 의하여 시각적인 표현이 가능하게 되었다. 그러나 visual cryptography는 표현의 한계로 응용범위가 극히 제한되었다. 이 논문에서는 visual cryptography의 응용범위를 수학에서 광학으로 확장하기 위하여 binary computer generated hologram을 encryption하는 방법을 제시하고 security 특성을 분석한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1169-1174
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• 2001

A new approach for determining global threshold value of binary image is proposed in this paper. In the proposed algorithm, bit-plane information which involve the shapes of original image is used for dividing image into two parts; object and background. Optimal threshold value are selected based on difference values of average between two regions, which is considered in global binary thresholding. Proposed method is no need to set a initial value, and consequently, it is relatively simple as well as robust. Experimental results showed a good performance in preserving edge not only continuous tone images but also document image.

• Proceedings of the IEEK Conference
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• summer
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• pp.438-441
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• 2004

Image binarization using a global threshold value [3] performs at high speed, but usually results in undesired binary images when the source images are of poor quality. In such cases, adaptive local thresholding algorithms [1][2][3] are used to obtain better results, and the algorithm proposed by A.E.Savekis which chooses local threshold using fore­ground and background clustering [1] is one of the best thresholding algorithms. However, this algorithm runs slowly due to its re-computing threshold value of each central pixel in a local window MxM. In this paper, we present a dynamic programming approach for the step of calculating local threshold value that reduces many redundant computations and improves the execution speed significantly. Experiments show that our proposal improvement runs more ten times faster than the original algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.94-102
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• 2007

In de-noising, it is wellknown that wavelet-thresholding algorithm shows near-optimal performances in the minimax sense. However, the wavelet-thresholding algorithm is difficult in realization it on hardware, such as FPGA, because of wavelet function complexity. In this paper, we present a new do-noising technique with the binary tree structured filter bank, which is based on the signal power ratio of each subbands to the total signal power. And we realize it on FPGA. For simple realization, the filter banks are designed by Hadamard transform coefficients. The simulation and hardware experimental results show that the performance of the proposed method is similar with that of soft thresholding de-noising algorithm based on wavelets, nevertheless it is simple.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.224-230
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• 2002

In this paper, a counting algorithm hybridized with an adaptive automatic thresholding method based on Otsu's method and the algorithm that elongates markers obtained by the well-known watershed algorithm is proposed to enhance the exactness of the microcell counting in microscopic images. The proposed counting algorithm can be stated as follows. The transformed full image captured by CCD camera set up at microscope is divided into cropped images of m$\times$n blocks with an appropriate size. The thresholding value of the cropped image is obtained by Otsu's method and the image is transformed into binary image. The microbial cell images below prespecified pixels are regarded as noise and are removed in tile binary image. The smoothing procedure is done by the area opening and the morphological filter. Watershed algorithm and the elongating marker algorithm are applied. By repeating the above stated procedure for m$\times$n blocks, the m$\times$n segmented images are obtained. A superposed image with the size of 640$\times$480 pixels as same as original image is obtained from the m$\times$n segmented block images. By labeling the superposed image, the counting result on the image of microbial cells is achieved. To prove the effectiveness of the proposed mettled in counting the microbial cell on the image, we used Acinetobacter sp., a kind of ammonia-oxidizing bacteria, and compared the proposed method with the global Otsu's method the traditional watershed algorithm based on global thresholding value and human visual method. The result counted by the proposed method shows more approximated result to the human visual counting method than the result counted by any other method.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.311-314
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• 1995

This paper presents a method for measuring tool wear parameters based on two dimensional image information. The tool wear images were obtained from an ITV camera with magnifying and lighting devices, and were analyzed using image processing techniques such as thresholding, noise filtering and boundary tracing. Thresholding was used to transform the captured gray scale image into a binary image for rapid sequential image processing. The threshold level was determined using a novel technique in which the brightness histograms of two concentric windows containing the tool wear image were compared. The use of noise filtering and boundary tracing to reduce the measuring errors was explored. Performance tests of the measurement precision and processing speed revealed that the direct method was highly effective in intermittent tool wear monitoring.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.341-349
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• 2008

This study proposes new automatic thresholding method, which is important step for detecting binary change/non-change information using satellite images. Result value through pixel-based similarity measurement is calculated cumulatively with regular interval, and thresholding is pointed at the steep slope position. The proposed method is assessed in comparison with expectation-maximization algorithm and coner method using synthetic images, ALI images, and Hyperion images. Throughout the results, we validated that our method can guarantee the similar accuracy with previous algorithms. It is simpler than EM algorithm, and can be applied to the binormal histogram unlike the coner method.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.842-851
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• 1996

Median filter(MF) has often been applied to color or gray images as a noise fiilter in image processing . Application of MF to binary images was tried in this study. For binary images, MF not only can remove noise but can also work as an indicator showing the dominant color in a region which is called window . Fro example, MF can be used to categorize clusters and to detect interested parts of an object. In other words, MF can also be used to remove unnecessary parts. The function of MF can be intensified by introducing a thresholding value, which is determined by the size of the interested part of an object. This improved MF for binary images is called the modified median filter(MMF), and its applicability to grade produce will be discussed in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.950-956
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• 2014

In this paper, the real-time detection method of a DDP (Driving Direction Point) is proposed for an unmanned vehicle to safely follow the center of the road. Since the DDP is defined as a center point between two lanes, the lane is first detected using a web camera. For robust detection of the lane, the binary thresholding and the labeling methods are applied to the color camera image as image preprocessing. From the preprocessed image, the lane is detected, taking the intrinsic characteristics of the lane such as width into consideration. If both lanes are detected, the DDP can be directly obtained from the preprocessed image. However, if one lane is detected, the DDP is obtained from the inverse perspective image to guarantee reliability. To verify the proposed method, several experiments to detect the DDPs are carried out using a 4 wheeled vehicle ERP-42 with a web camera.

• ETRI Journal
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• v.28 no.1
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• pp.51-58
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• 2006

In this paper, we propose a method of applying a lifting-based wavelet domain e-median filter (LBWDEMF) for image restoration. LBWDEMF helps in reducing the number of computations. An e-median filter is a type of modified median filter that processes each pixel of the output of a standard median filter in a binary manner, keeping the output of the median filter unchanged or replacing it with the original pixel value. Binary decision-making is controlled by comparing the absolute difference of the median filter output and the original image to a preset threshold. In addition, the advantage of LBWDEMF is that probabilities of encountering root images are spread over sub-band images, and therefore the e-median filter is unlikely to encounter root images at an early stage of iterations and generates a better result as iteration increases. The proposed method transforms an image into the wavelet domain using lifting-based wavelet filters, then applies an e-median filter in the wavelet domain, transforms the result into the spatial domain, and finally goes through one spatial domain e-median filter to produce the final restored image. Moreover, in order to validate the effectiveness of the proposed method we compare the result obtained using the proposed method to those using a spatial domain median filter (SDMF), spatial domain e-median filter (SDEMF), and wavelet thresholding method. Experimental results show that the proposed method is superior to SDMF, SDEMF, and wavelet thresholding in terms of image restoration.