• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.67-72
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• 2005

Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.1-8
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• 2006

This paper proposes an improved FCM(Fuzzy C-means) algorithm using intercluster and entropy-based weight in gray image. The fuzzy clustering methods have been extensively used in the image segmentation since it extracts feature information of the region. Most of fuzzy clustering methods have used the FCM algorithm. But, FCM algorithm is still sensitive to noise, as it does not include spatial information. In addition, it can't correctly classify pixels according to the feature-based distributions of clusters. To solve these problems, we applied a weight and intercluster to the traditional FCM algorithm. A weight is obtained from the entropy information based on the cluster's number of neighboring pixels. And a membership for one pixel is given based on the information considering the feature-based intercluster. Experiments has confirmed that the proposed method was more tolerant to noise and superior to existing methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.66-73
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• 2006

Safety is the most important for all traffic management and control technology. This paper focuses on developing a flexible, reliable and real-time processing algorithm which is able to generate signal for the entering vehicle at the joining road through a camera and image processing technique. The images obtained from the camera located beside and upon the road can be used for traffic surveillance, the vehicle's travel speed measurement, predicted arriving time in joining area between main road and joining road. And the proposed algorithm displays the confluence safety signal with red, blue and yellow color sign. The three methods are used to detect the vehicle which is driving in setted detecting area. The first method is the gray scale normalized correlation algorithm, and the second is the edge magnitude ratio changing algorithm, and the third is the average intensity changing algorithm The real-time prototype confluence safety signal generation algorithm is implemented on stored digital image sequences of real traffic state and a program with good experimental results.

• Imaging Science in Dentistry
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• v.32 no.4
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• pp.201-206
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• 2002

Purpose : To evaluate the radiographic change of operation sites after orthognathic surgery using the digital image processing and fractal analysis. Materials and Methods : A series of panoramic radiographs of thirty-five randomly selected patients who had undergone mandibular orthognathic surgery (bilateral sagittal split ramus osteotomy) without clinical complication for osseous healing, were taken. The panoramic radiographs of each selected patient were taken at pre-operation (stage 0), 1 or 2 days after operation (stage 1), 1 month after operation (stage 2), 6 months after operation (stage 3), and 12 months after operation (stage 4). The radiographs were digitized at 600 dpi, 8 bit, and 256 gray levels. The region of interest, centered on the bony gap area of the operation site, was selected and the fractal dimension was calculated by using the tile-counting method. The mean values and standard deviations of fractal dimension for each stage were calculated and the differences among stage 0, 1, 2, 3, and 4 were evaluated through repeated measures of the ANOVA and paired t-test. Results : The mean values and standard deviations of the fractal dimensions obtained from stage 0, 1, 2, 3, and 4 were 1.658±0.048, 1.580±0.050, 1.607±0.046, 1.624±0.049, and 1.641 ±0.061, respectively. The fractal dimensions from stage 1 to stage 4 were shown to have a tendency to increase (p < 0.05). Conclusion: The tendency of the fractal dimesion to increase relative to healing time may be a useful means of evaluating post-operative bony healing of the osteotomy site.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• The Journal of Information Technology
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• v.5 no.4
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• pp.115-127
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• 2002

This paper proposes improved file encryption algorithm which represents image of grayscale type not using proper cover image for ciphertext. This method consists of 3-Tire encryption steps. 1-Tire and 2-Tire encrypt the information using existed stream algorithm and block algorithm with modyfied padding method. We propose the MBE method as 3-Tire, which hides structure and format of encrypted file. The proposed method outputs grayscale file as the result of encryption and since many GSF outputs resulted from different kinds plaintexts, have similar patterns. we obtain both file encryption and hiding the file information. Also, to solve the problem of padding in block algorithm, we propose the new padding algorithm called SELI(Select Insert) and apply 2-Tire block algorithm and MBE algorithm used 3-Tire.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.267-270
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• 2016

Currently, tire has a variety of information to know the information of the tire are displayed on the tire side. the market are marked with raised letters showing a variety of information relating to the tires. Such information enables people and tire related companies to distinguish between tires upon the information marked on the tires. Generally, people see the information including max press, manufacturing date, etc. Accordingly, studies on automated recognition of raised letters on tire by using image processing technology have been presented consistently. However, they lack a method for recognition of letters and improvement of the recognition. Moreover, the raised letters have been previously recognized through image processing. Further, to obtain the character recognition of a conventional side in video, it is suitably utilized the effects of lighting time of acquisition, so as part of the background and the character has a gray level values between approximately the same, is the part that is not relatively clear are many scattered. In this paper, we see the characters of the tire side using the laser sensor, recognition, was designed for character recognition of the tire side.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.16-24
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• 2005

In this paper, we proposed a face tracking algorithm for a viewpoint adaptive multi-view synthesis system. The original scene captured by a depth camera contains a texture image and 8 bit gray-scale depth map. From this original image, multi-view images can be synthesized which correspond to viewer's position by using geometrical transformation such as a rotation and a translation. The proposed face tracking technique gives a motion parallax cue by different viewpoints and view angles. In the proposed algorithm, tracking of viewer's dominant face initially established from camera by using statistical characteristics of face colors and deformable templates is done. As a result, we can provide motion parallax cue by detecting viewer's dominant face area and tracking it even under a heterogeneous background and can successfully display the synthesized sequences.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.737-744
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• 2005

In this paper, we propose a three-level color clustering algerian for the binarization of text regions extracted from natural scene images. The proposed algorithm consists of three phases of color segmentation. First, the ordinary images in which the texts are well separated from the background, are binarized. Then, in the second phase, the input image is passed through a high pass filter to deal with those affected by natural or artificial light. Finally, the image Is passed through a low pass filter to deal with the texture in texts and/or background. We have shown that the proposed algorithm is more effective used gray-information binarization algorithm. To evaluate the effectiveness of the proposed algorithm we use a commercial OCR software ARMI 6.0 to observe the recognition accuracies on the binarized images. The experimental results on word and character recognition show that the proposed approach is more accurate than conventional methods by over $35\%$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.137-145
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• 2016

We are accustomed to using the word 'beautiful' when we see something, but we don't use the word 'sublime' very often. In fact, these two words have totally different meanings and we can say 'sublime' only for special objects. The notions and objects of sublime have been studied by numerous philosophers ranging from Longinus to Burke and Kant. According to their studies, we can feel sublimity from objects which give us fear, because the sublime is inherent in fear. Therefore, in this study, we considered the sublime in the gothic novel, A Rose for Emily, in which we can find solemn sublimity in Emily's iron gray hair, her black suit, and a red rose which stands for blood. In addition, we can feel sublimity in the image of Emily who is waiting for Homer and the image of Homer's dead body. These kinds of images instill us with fear, but also show us tragic sublimity. The sublime exists in all kinds of literature and, therefore, more studies and analyses of the sublime in literature will likely be conducted.