• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.333-336
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• 2002

This paper presents a new image segmentation method using fuzzy measures which reflect the local property of an image as well as the global property of an image An image is globally segmented into the crisp region and the ambiguous region in terms of the Index of fuzziness measured over all pixels of an image. The ambiguous region is luther partitioned into background and object in terms of the index of fuzziness computed over the set of neighboring pixels reflecting the local property most. From the experimental results, this method shows the effective ambiguity handling capability in segmenting an image.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.181-183
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• 2004

In this paper, We proposed an algorithm which extraction iris region from 2D image. Our method is composed of three parts : internal boundary defection and external boundary detection. Since eyelid and eyelash cover part of the boundary and the size of iris changes continuously, it is difficult to extract iris region accurately. For the interior and exterior boundary detection, we used partial differentiation of histogram. Performance of the proposed algorithm is tested and evaluated using 360 iris image samples.

• 한국멀티미디어학회논문지
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• 제18권10호
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• pp.1172-1179
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• 2015

A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.

• Journal of Multimedia Information System
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• 제4권1호
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• pp.43-50
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• 2017

In this paper, we propose a method which detects the nose and face of certain human by using the depth image. The proposed method has advantages of the low computational complexity and the high accuracy even in dark environment. Also, the detection accuracy of nose and face does not change in various postures. The proposed method first locates the locally protruding part from the depth image of the human body captured through the depth camera, and then confirms the nose through the depth characteristic of the nose and surrounding pixels. After finding the correct pixel of the nose, we determine the region of interest centered on the nose. In this case, the size of the region of interest is variable depending on the depth value of the nose. Then, face region can be found by performing binarization using the depth histogram in the region of interest. The proposed method can detect the nose and the face accurately regardless of the pose or the illumination of the captured area.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.801-802
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• 2008

This paper presents a new dynamic range compression method using region-adaptive gamma correction. Gamma corrections with different gamma coefficients are first applied to the observed image to generate several candidate images. Then, the proposed method produces the result image by adequately combining them according to the weight function based on local variances. Experimental results demonstrate that the proposed method significantly enhances image quality by bringing out the details not only in dark region but also in bright region.

• 한국정보통신학회논문지
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• 제3권3호
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• pp.597-605
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• 1999

본 논문에서는 조영제 투입이전의 초기영상과 조영제가 투입된 현재 프레임을 감산하는 방법을 사용하여 영역 분할을 하고 심장조영상을 압축하는 기법을 제안한다. 차영상에서 안정영역을 얻기 위하여 다중 임계값을 도입하며, 안정영역의 영상에서 의미영역을 추출하고 이를 경계와 질감정보로 분류한다. 경계정보는 경계 부호화하고, 질감정보는 2차원 근사 다항식으로 근사화하여 그 계수를 부호화한다. 실험결과, 심장조영상에 대해 고압축율을 이룩하였고, 0.02∼0.04 bpp의 전송율로 좋은 재생영상을 얻었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1495-1498
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• 2002

The constrained average method is one of dither methods which combines edge emphasis and grayscale rendition to provide legibility of textual region and proper quality of continuous tone region. How-ever, image quality of continuous tone region is insufficient compared to other dither methods, such as ordered dither methods or the error diffusion method. The constrained average method uses a uniform distribution function to decide number of lit pixels related to the average intensity in a picture area. However, actual distribution of continuous tone region is closer to the Laplacian distribution or triangle distribution. In this paper, we introduce various probability distributions and the actual luminance distribution to decide the threshold value of the constrained average method in order to improve image quality of dithered image.

• 한국군사과학기술학회지
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• 제11권4호
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• pp.107-115
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• 2008

Accurate extraction of traversable region is a critical issue for autonomous navigation of unmanned ground vehicle(UGV). This paper introduces enhanced extraction of traversable region by combining scene clustering with 3D world modeling using CCD(Charge-Coupled Device)/IR(Infra Red) image. Scene clustering is developed with K-means algorithm based on CCD and IR image. 3D world modeling is developed by fusing CCD and IR stereo image. Enhanced extraction of traversable regions is obtained by combining feature of extraction with a clustering method and a geometric characteristic of terrain derived by 3D world modeling.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.192-194
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• 2003

Since the details in quasi-homogeneous region will be destroyed from the conventional global image enhancement method such as histogram equalization. This defect is caused by the saturation of gray level in equalization process. So the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the region itself. To obtain the quasi- homogeneous regions, the original image must be segmented. Here we applied the watershed transform to the interesting image. Since the watershed transform is based on mathematical morphology, therefore, the regions touch can be effectively separated. Hence two adjacent regions which have the similar gray pixels will be split off. The process will be independently applied to three different spectral images. Then three different colors are assigned to each processed image in order to produce a color composite image. By the proposed algorithm, the result image shows the better perception on image details. Therefore, the high efficiency of image classification can be obtained by using this color image.

• 정보처리학회논문지B
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• 제12B권5호
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• pp.587-594
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• 2005

본 논문은 전이 영역에서 퍼지 클러스터링 알고리즘을 이용한 multi-level thresholding 방법을 제안한다. 대부분의 임계치 기반 영상 분할은 영상의 히스토 그램 분포를 기반으로 임계치를 결정한다. 그러므로 많은 처리시간과 기억공간을 요구할 뿐만 아니라 복잡하고 무분별한 히스토 그램 분포를 가지는 실영상에서의 임계치 결정에는 어려움이 있다. 본 논문에서는 영상의 대표적인 성분들로 구성된 전이 영역을 추출한 후 퍼지 클러스터링 알고리즘에 의해 최적의 임계치를 결정한다. 전이 영역을 추출하기 위해 이용되는 지역적 엔트로피는 잡음에 강건하며 영상에 내재된 정보를 잘 표현한다는 특성을 가진다. 그리고 퍼지 클러스터링 알고리즘은 복잡하고 무분별한 분포의 실영상에 대해서도 정확히 임계치를 설정할 수 있으며 multi-level thresholding으로 쉽게 확장이 가능하다. 다양한 실영상을 대상으로 실험한 결과, 제안한 방법이 기존의 방법보다 향상된 성능을 가짐을 보였다.