• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.626-628
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• 2016

본 논문에서는 이진 영상에서 일부 정보가 손실된 경우에 히스토그램을 분석하여 구간을 분할한 후, 오츠 이진화와 퍼지 이진화 기법을 적용하여 원 영상을 이진화 한 후에 홉필드 네트워크를 적용하여 영상을 복원하는 방법을 제안한다. 제안된 방법은 그레이 영상에서 히스토그램을 분석하여 픽셀 값의 변화의 폭이 큰 부분들을 분석하여 구간들을 분할하고 변화의 폭이 큰 부분의 지점에 속하는 영역은 오츠 이진화 기법을 적용하여 이진화하고 그 외의 구간들은 퍼지 이진화 기법을 적용하여 영상을 이진화 한다. 그리고 이진화 된 영상을 홉필드 네트워크를 적용하여 학습한다. 실험 영상에 정보 손실이 발생한 영상을 대상으로 제안된 방법을 적용한 결과, 대부분의 정보 손실이 있는 영상에서 모두 복원되는 것을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.865-871
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• 2022

In this paper, we propose a method of extracting prostate region using morphological characteristics of ultra-sonic image of prostate. In the first step of the proposed method, the edge area of the prostate image is extracted. The histogram of ultra-sonic image is used to extract base objects to detect the upper edge of prostate region by altering the contrast of the image, then, the lower edges of the extracted base objects are connected by using monotone cubic spline interpolation to extract the upper edge. Step 2, Otsu's binarization is applied to the region under the extracted upper edge of the prostate ultra-sonic image to extract the lower edge of prostate. In the last step, the upper and the lower edges are connected to extract prostate region and by comparing the extracted region of prostate with the one measured manually, the result showed that the morphological characteristics of prostate in ultrasonic image can be utilized to extract the prostate region.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.405-407
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• 1997

본 논문은 자동차 번호판 용도문자를 인식하개 위한 전처리 과정으로써 웨이브릿 변환을 적용한 연구에 관해 기술한다. 웨이브릿 변환에 의하여 여과된 고주파 대역의 영상은 수평방향, 수직방향, 대각선 방향의 윤관석 형태로 세 개의 대역에 존재하게 되는데, 대상영상이 고주파 대역의 에너지량이 적게 나타나는 반면에 저주파 대역의 에너지량은 크므로 용도문자의 인식 과정에서 저주파 대역 부분만을 이용하였다. 저주파 대역에서 $20{\times}20$크기의 영상을 추출하고 영상을 정규화 하여 오츠알고리즘을 통한 이치화 과정을 거친 다음 역전파 신경망으로 인식함으로써 기존의 단순축소 방법보다 향상된 결과를 실험을 통하여 확인할 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.347-352
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• 2011

Entropy used for measuring the richness in details of the image and absolute mean brightness error(AMBE) providing a change in the image global appearance are two quantitative measures generally used for measuring quality of images. In this paper, we propose an entropy and AMBE-based thresholding method to binalize a given image. The effectiveness of the proposed method is demonstrated by thresholding experiments on nine test images and comparison with other conventional thresholding methods, that is, Otsu method and entropy-based method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.511-513
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• 2016

본 논문에서는 세라믹 영상에서 사람의 눈으로 판단하기 어려운 결함 영역을 검출하기 위해 배경을 제거한 후에 지역 기반 오츠 이진화와 양방향 소벨 마스크를 적용하여 세라믹 영상의 윤곽선을 검출한다. 윤곽선이 검출된 영상을 수평으로 4등분하고, 각각의 영역에서 밝기 값이 변화는 지점을 탐색한다. 탐색된 좌표 중에서 최대 명암도 값을 이용하여 ROI 영역을 추출한다. 결함 영역 검출의 효율성을 높이기 위한 전 단계로 배경을 제거하기 위해 ROI 영역과 최소값 필터가 적용된 ROI 영역 간의 명암도의 차이를 이용하여 배경을 제거한다. 명암도의 차이를 통해 배경이 제거된 ROI 영역에서 개선된 명암 대비 스트레칭 기법을 적용하여 ROI 영역의 명암 대비를 강조한다. 명암이 강조된 ROI 영역에서 10mm, 11mm, 16mm, 22mm 영상의 결함 영역을 검출하기 위해 히스토그램 이진화 기법을 적용하여 결함의 후보 영역을 추출한다. 결함 후보 영역이 검출된 ROI 영역에서 미세 잡음을 제거하기 위해 중간값 필터와 침식과 팽창을 적용한 후에 최종적인 결함 영역을 검출한다. 제안된 방법을 8mm, 10mm, 11mm, 16mm, 22mm 세라믹 영상을 대상으로 실험한 결과, 제안된 검출 방법이 기존의 검출 방법보다 모든 mm 세라믹 영상에서 효과적으로 결함 영역이 검출되는 것을 확인하였다.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1305-1318
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• 2012

Image segmentation is one of the difficult research problems in machine vision and pattern recognition field. A commonly used segmentation method is the Otsu method. It is simpler and easier to implement but it fails if the histogram is unimodal or similar to unimodal. And if some target area is smaller than background object, then its histogram has the distribution close to unimodal. In this paper, we proposed an improved image segmentation method based on 1D Otsu method for a small target detection. To overcome drawbacks by unimodal histogram effect, we depressed the background histogram using a logarithm function. And to improve a signal to noise ratio, we used a local average value by the neighbor window for thresholding using 1D Otsu method. The experimental results show that our proposed algorithm performs better segmentation result than a traditional 1D Otsu method, and needs much less computational time than that of the 2D Otsu method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1414-1419
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• 2015

A method for detecting a skin region on the image is generally used to detect the color information. However, If saturation lowered, skin detection is difficult because hue information of the pixels is lost. So in this paper, we propose a method of correcting color of lower saturation of skin region images by the lighting. Color correction process of this method is saturation image acquisition and low-saturation region classification, segmentation, and the saturation of the split in the low saturation region extraction and color values, the color correction sequence. This method extracts the low saturation regions in the image and extract the color and saturation in the region and the surrounding region to produce a color similar to the original color. Therefore, the method of extracting the low saturation region should be correctly preceding. Because more accurate segmentation in the process of obtaining a low saturation regions, we use a multi-threshold method proposed Otsu in Hue values of the HSV color space, and create a binary image. Our experimental results for 170 portrait images show a possibility that the proposed method could be used efficiently preprocessing of skin color detection method, because the detection result of proposed method is 5.8% higher than not used it.

• Journal of the Korea Convergence Society
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• v.8 no.6
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• pp.283-289
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• 2017

This study examines the impact of dance in dance viral convergence advertising. Dance viral images appeal to a wide range of consumers. Especially, Dong-A Otsuka's Oronamin C ad released in 2015 achieved great results and won an advertisement award with an addictive CM song and dance. So this study selected the advertisements of Oronnamin C from 2015 to 2017 for its analysis. The theoretical background is analyzed through the element of dance choreography and characteristics. The results of the analysis of ads showed that they were made of simple and repetitive situations, which are the characteristics of dance comic style. There was little shift in space, choreography was mainly based on one straight line but with a crowded group, circle and V-shape appeared. Spatial composition was mainly first-person point of view. In the dance viral ads , dances were composed of short rhythmic phrases with simple and repetitive elements, eliminating complicated elements.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.107-114
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• 2022

In order to classify 3D film images as right or wrong, it is necessary to detect the pattern in a 3D film image. However, if the contrast of the pixels in the 3D film image is low, it is not easy to classify as the right and wrong 3D film images because the pattern in the image might not be clear. In this paper, we propose a method of classifying 3D film images as right or wrong by comparing the width at a specific frequency of each histogram after obtaining the histogram. Since, it is classified using the width of the histogram, the analysis process is not complicated. From the experiment, the histograms of right and wrong 3D film images were distinctly different, and the proposed algorithm reflects these features, and showed that all 3D film images were accurately classified at a specific frequency of the histogram. The performance of the proposed algorithm was verified to be the best through the comparison test with the other methods such as image subtraction, otsu thresholding, canny edge detection, morphological geodesic active contour, and support vector machines, and it was shown that excellent classification accuracy could be obtained without detecting the patterns in 3D film images.