• The Journal of the Korean dental association
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• v.47 no.10
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• pp.669-676
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• 2009

Purpose : Anterior region is crucial area for esthetic implant restoration. However, the alveolar process undergoes atrophy after removal of teeth and creates unfavorable situation for implant installation. The knowledge of the thickness of alveolar bone is required to estimate and expect the bone resorption after extraction. The aim of this study is to measure facial, palatal and faciopalatal bone thickness on maxillary anterior teeth. Methods : Facial, palatal, and faciopalatal bone thickness were measured on the computed tomography (CT) images from 57 patients, using an image analyzer program (Ondemand$3D^{(R)}$, Cybermed, Seoul, Korea). Results : The thickness of facial bone in incisors, lateral incisors and canines were less than 1 mm. The thickness of facial bone increased from anterior to posterior region and the thickness of palatal bone increased from posterior to anterior region. Conclusion : The measurement can be used for planning implant surgery before extraction. CT has are clinically useful in the evaluation of thickness of alveolar bone.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.31-39
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• 2010

In some image processing system or the users who want to see a specific region of image simply, if a part of the image has higher quality than other regions, it would be a nice service. Specifically in mobile environments, preferential service was needed, as the screen size is small. So, JPEG2000 supplies this function. But this doesn't support the process to extract specific regions or service and does the functions to add some techniques. It is called by ROI(Region-of-Interest). In this paper, we use images including human faces, which are processed most preferentially and compressed with high quality. Before an image is served to the users, it is compressed and saved. Here, the face parts are compressed with higher quality than the background which are relatively with lower quality. This technique can offer better service with preferential transferring of the faces, too. Besides, whole regions of the image are compressed with same quality and after searching the faces, they can be preferentially transferred. In this paper, we use a face extraction approach based on neural network and the preferential processing with EBCOT of JPEG2000. For experimentation, we use images having several human faces and evaluate objectively and subjectively, and proved that this approach is a nice one.

• Journal of Environmental Impact Assessment
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• v.3 no.2
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• pp.15-24
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• 1994

The goal of impact studies (e.g., as mandated by NEPA in the USA) is to ensure that the full implications of development proposals (ecologic, economic, and social) are taken into account before decisions are made and projects are allowed to proceed. In other words, the aim is to ensure that impact assessment is integrated into planning and policy processes. Today. nearly 25 years after the enactment of NEPA, it is appropriate to inquire regarding the extent of progress toward such integration. This paper examines the role of impact assessment in planning and policy processes with specific reference to resource development projects in the Great Plains region of the USA. The author gives special attention to the socioeconomic impacts associated with energy resource extraction and conversion projects and the role of impact assessment in project evaluation, in local and regional planning, and in state policy development.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.33-36
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• 2001

With all the researches to define human genom and to look for some new bio-activated material in the bio-technology field recently, it is more highly needed to analyse DNA or so called Material than ever before. First, the lanes are extracted based on histogram analysis and projection technique. And then three other approaches are applied for band extraction: SB, RG-1, and RG-2. In SB method, a search line is set dividing each lane equally and vertically to find peaks and valleys. And according to them, minimum enclosing rectangle of each band is determined. In RC-1 approach, on the other hand, band areas are extracted by region growing with the peaks as seeds, avoiding the overlap with the neighboring bands. In RC-2 approach, peaks and valleys are searched in two lines that trisect the lane vertically, and the pair of peaks in the same band are determined, and then used to grow the region. To compare the accuracy of the three suggested methods, we measure the location and amount of bands. The result shows that the mean deviation of the location is 0.06, 0.03, and 0.01 for SB, RG-1, and RC-2 respectively. And the mean deviation of the amount of bands is 0.08, 0.05, and 0.02 for SB, RG-1, and RG-2 respectively. In conclusion, the RG-2 method suggested in this paper appears to be the most reliable on the degree of the accuracy in measuring the location and amount of bands

• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.275-282
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• 2013

This paper proposes a method for human identification using teeth contours extracted from dental images that are captured from the frontal views of subjects each of who opens his or her mouth slightly. Each dental image has a black-colored region containing the subject's teeth contours which are usually different from subject to subject. This means that this black-colored region has bio-mimetic information useful for human identification. The basic idea of the method is to extract the upper and lower teeth contours from the dental image of each subject and to encode their geometric patterns using a back-propagation neural network model. After acquiring 400 teeth images form 10 university students, we used 300 images for the training data of the neural network model and 100 images for its verification. Experimental results have shown that the proposed neural network-based method can be used as an alternative solution for identification among a small group of humans with a low cost and simple setup.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.661-672
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• 2008

In this paper an algorithm, based on extracting a certain target of an image, is proposed that is capable of performing bilevel thresholding of image with multimodal distribution. Each pixel in the image has a membership value which is used to denote the characteristic relationship between the pixel and its belonging region (i.e. the object or background). Using the membership values of image set, a new measurement, which simultaneously measures the measure of fuzziness and the conditional entropy of the image, is calculated. Then, thresholds are found by optimally minimizing calculated measurement. In addition, a fuzzy range is defined to improve the threshold values. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively extract the meaningful target from the input image. The resulting image can preserve the object region we target very well.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1287-1292
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• 2005

This paper presents an effective pattern classification model by designing an artificial neural network based pattern classifiers for face recognition. First, a RGB image inputted from a frame grabber is converted into a HSV image which is similar to the human beings' vision system. Then, the coarse facial region is extracted using the hue(H) and saturation(S) components except intensity(V) component which is sensitive to the environmental illumination. Next, the fine facial region extraction process is performed by matching with the edge and gray based templates. To make a light-invariant and qualified facial image, histogram equalization and intensity compensation processing using illumination plane are performed. The finally extracted and enhanced facial images are used for training the pattern classification models. The proposed H-ART2 model which has the hierarchical ART2 layers and F-LVQ model which is optimized by fuzzy membership make it possible to classify facial patterns by optimizing relations of clusters and searching clustered reference patterns effectively. Experimental results show that the proposed face recognition system is as good as the SVM model which is famous for face recognition field in recognition rate and even better in classification speed. Moreover high recognition rate could be acquired by combining the proposed neural classification models.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.383-389
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• 2016

This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.6
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• pp.711-720
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• 2015

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance have been reported. Since several pixels per an object may be generated in a close-range radar application, a width of an object can be estimated automatically by various signal processing techniques. In this paper, we tried to attempt to develop an algorithm to estimate obstacle width using Radar images. The proposed method consists of 5 steps - 1) background clutter reduction, 2) local peak pixel detection, 3) region growing, 4) contour extraction and 5)width calculation. For the performance validation of our method, we performed the test width estimation using a real data of two cars acquired by commercial radar system - I200 manufactured by Navtech. As a result, we verified that the proposed method can estimate the widths of targets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8C
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• pp.783-792
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• 2005

This paper proposes a feature extraction method for sketch-based image retrieval of animation character. We extract the specific regions using the detection of scene change and correlation points between two frames, and the property of animation production. We detect the area of focused similar colors in extracted specific region. And it is used as feature descriptor for image retrieval that focused color(FC) of regions, size, relation between FCs. Finally, an user can retrieve the similar character using property of animation production and user's sketch as a query Image.