• 한국컴퓨터그래픽스학회논문지
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• 제16권1호
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• pp.1-7
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• 2010

비전 기반의 감시 시스템에서 동일인의 식별은 매우 중요하다. 감시 시스템에서 주로 사용되는 CCTV 카메라의 영상은 상대적으로 낮은 해상도를 가지므로 얼굴 인식 기법을 이용하여 동일인을 식별하기는 어렵다. 본 논문에서는 CCTV 카메라 영상에서 의상 특징을 이용하여 동일인을 식별하는 알고리즘을 제안한다. 건물의 주출입구에서 출입자가 인증을 받을 때, 의상 특징이 데이터베이스에 저장된다. 그 후, 건물 내에서 촬영한 영상에 대해 배경 차감 및 피부색 발견 기법을 이용하여 의상 영역을 발견한다. 의상의 특징 벡터는 텍스처와 색상 특징을 이용하여 구성한다. 텍스처 특징은 지역적 에지 히스토그램을 이용하여 추출된다. 색상 특징은 색상 지도의 옥트리 기반 양자화(octree-based quantization)를 이용하여 추출된다. 건물 내의 촬영 영상이 주어질 때, 데이터베이스에서 의상 특징이 가장 유사한 사람을 발견함으로써 동일인을 식별하며, 의상 특징 벡터 간의 유사도 측정을 위해서는 유클리디안 거리(Euclidean distance)를 사용한다. 실험 결과, 얼굴인식 기법이 최대 43%의 성공률을 보인 데 비해, 의상 특징을 이용하여 80%의 성공률로 동일인을 식별하였다.

• 한국축산시설환경학회지
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• 제5권2호
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• pp.93-100
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• 1999

Pig's original image data was transformed to a binary image, an image excluding head and tail portion from the whole binary image, and a projected image associated with pig's height. Then the length of body, width of shoulder, and area of pig were calculated and the relationships among the above characteristics and pig's weight were analyzed. The results obtained from this study were as follows: 1. Whole binary image data was considered to be improper to determine the pig's weight because the movement of pig's head and tail portion affected the image data. 2. Binary image data excluding head and tail portion from the whole binary image showed a better estimation of the pig's weight than the whole binary image. 3. Pig's should width was analyzed to be improper factor to determine the pig's weight. 4. The projected image associated with pig's height showed the highest correlation between the pig's area of the image and pig's weight(R2=0.9965). From this research the projected image associated with pig's height, which is excluding head and tail portion from the whole body of pig's image, was considered to be the prime factor to measure the pig's weight by the noncontact measurement.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2213-2216
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• 2003

In this paper, we propose the face identification method which is robust for lighting based on the feature points method. First of all, the proposed method extracts an edge of facial feature. Then, by the hough transform, it determines ellipse parameters of each facial feature from the extracted edge. Finally, proposed method performs the face identification by using parameters. Even if face image is taken under various lighting condition, it is easy to extract the facial feature edge. Moreover, it is possible to extract a subject even if the object has not appeared enough because this method extracts approximately the parameters by the hough transformation. Therefore, proposed method is robust for the lighting condition compared with conventional method. In order to show the effectiveness of the proposed method, computer simulations are done by using the real images.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.435-437
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• 2004

This paper presents a personal identification method using teeth images. The method uses images for teeth expressions of anterior and posterior occlusion state and LDA-based technique. Teeth images give merits for recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, personal identification for 12 people was successful. It was shown that our method can contribute to multi-modal authentication systems.

• 한국멀티미디어학회논문지
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• 제23권9호
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• pp.1155-1163
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• 2020

Deep learning approach is emerging as a new way to improve the accuracy of tree species identification using bark image. However, the approach has not been studied enough because it is confronted with the problem of acquiring a large volume of bark image dataset. This study solved this problem by utilizing a pretrained off-the-shelf DCNN model. It compares the discrimination power of bark features extracted by each DCNN model. Then it extracts the features by using a selected DCNN model and feeds them to a multi-layer perceptron (MLP). We found out that the ResNet50 model is effective in extracting bark features and the MLP could be trained well with the features reduced by the principal component analysis. The proposed approach gives accuracy of 99.1% and 98.4% for BarkTex and Trunk12 datasets respectively.

• 한국가구학회지
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• 제26권3호
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• pp.274-285
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• 2015

Wood carving has been extremely widely practiced, but survives much less well than the other main materials, being vulnerable to decay, insect damage, and fire. It therefore forms an important hidden element in the art history of many cultures. Even though wood is less durable than either steel or stone, it has been used for a long time due to its usefulness. Wood has a lot of benefits. So people have used wood for materials in houses, trains, cars, bridges, and simple utilities in their ways according to their own religions, climates, and environment they are living in. Nowadays, there are wood products that are made up for its weaknesses and this has made wood be used in variety fields. Moreover, wood has been widely selected materials for sculptures, interior, and also for architecture thanks to its colors and textures. Wood has helped our life more abundant and beautiful.

• 한국정밀공학회지
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• 제19권12호
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• pp.100-108
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• 2002

This paper describes the development of adult authentication system using numerical recognition. Nowadays, the automats are very popular and they are dealing in many item suck as coffee, soft drinks, alcoholic drinks and cigarettes, etc. Among these items, some are harmful to the minor, and so the sale of these to the minor must be prohibited. In relation to this, adult authentication system is required to be equipped to the automat which deals in items harmful to minor. According to these demands, we develop the adult authentication system. This system capture the image of a residence certificate card by the identification card-reader, and recognize its numbers and identify it as adult or minor by main computer, where numeral recognition is accomplished by using image processing methods and neural network recognizer. The characteristic test of the system is carried out, and its result reveals that the system has the error of less than 1%. Thus, It is thought that the system can be used for identifying adult in the automats.

• 전자공학회논문지B
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• 제30B권8호
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• pp.1-7
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• 1993

This paper proposed an algorithm that extracts the optimum characteristics parameters to identify the signatures from the spectrum using 2-D FFT. The signature image input through a scanner is normalized into 250*128 pixels in the prepocessor. Normalized image is divided into block segments and each segment is transformed into space spectrum by 2-d FFT. There are several methods extracting the signature characteristic parameters from that spectrum. The result of experimentations which use the characteristic parameters extracted between $0^{\circ}and\;90^{\circ}$ in (0, 0), (63, 0) corners from 64$\times$64 block spectrum shows that the signature identification rate using that method gives 92.5% of successful achievement for 100 signatures, higher than the others.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.164-169
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• 2009

As one of the most interesting scenes, landmarks constitute a large percentage of the vast amount of scene images available on the web. On the other hand, a specific "landmark" usually has some characteristics that distinguish it from surrounding scenes and other landmarks. These two observations make the task of accurately estimating geographic information from a landmark image necessary and feasible. In this paper, we propose a method to identify landmark location by means of landmark recognition in view of significant viewpoint, illumination and temporal variations. We use GPS-based clustering to form groups for different landmarks in the image dataset. The images in each group rather fully express the possible views of the corresponding landmark. We then use a combination of edge and color histogram to match query to database images. Initial experiments with Zubud database and our collected landmark images show that is feasible.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.396-399
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• 2009

In this paper, we present a method to define a color similarity between color images using Octree-based quantization and similar color integration. The proposed method defines major colors from each image using Octree-based quantization. Two color palettes to consist of major colors are compared based on Euclidean distance and similar color bins between palettes are matched. Multiple matched color bins are integrated and major colors are adjusted. Color histogram based on the color palette is constructed for each image and the difference between two histograms is computed by the weighted Euclidean distance between the matched color bins in consideration of the frequency of each bin. As an experiment to validate the usefulness, we discriminated the same clothing from CCD camera images based on the proposed color similarity analysis. We retrieved the same clothing images with the success rate of 88 % using only color analysis without texture analysis.