• 한국정밀공학회지
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• 제19권2호
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• pp.151-159
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• 2002

The method of accumulating a sequence of focused images is usually used for reconstruction of 3D object\\`s shape. To acquire a focused image, the conventional methods must calculate the focus measures of all pixels resulting in a long measurement time. This paper proposes a new method of reducing the computation time spent for deciding the focused pixels in the input image, which predicts the area in the image to calculate the focus measure based on a priori information on the object to be measured. The proposed algorithm estimates the area to consider in the next measurement based on the focused area in the present measurement. As the focus measure, Laplacian measure was used in this paper and the experiments have shown that the preposed algorithm may significantly reduce the calculation time. Although, as implied, this algorithm can be applied to only simple objects at this stage, advanced representation schemes will eliminate the restrictions on application domain.

• 정보저장시스템학회논문집
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• 제5권2호
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• pp.89-95
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• 2009

We setup the system to measure the noise characteristics of the 5M complementary metal-oxide semiconductor (CMOS) image sensor by generic measurement indicator of Standard mobile imaging architecture (SMIA) which is one of internal standard of mobile imaging architecture. To evaluate the effect of environment and setting parameters, such as temperature and integration time, we measure the variation of the dark signal, dynamic range and fixed pattern noise of image sensor. We also detect the number of defective pixels and cluster defects defined as adjacent single defect pixels at 5M CMOS image sensor. Then, we find the existence of some cluster defects in experiment, which are not expected in calculation.

• 정보관리학회지
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• 제16권4호
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• pp.95-107
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• 1999

색상에 의한 내용기반 이미지 검색에서는 이미지의 하위 영역을 구분하는 방식에 대하여 다양한 접근이 이루어져 왔다. 이러한 접근 방식 가운데 하나로 이미지를 다섯 개의 영역으로 나눈 뒤 일련의 검색 실험을 수행한 예를 들 수 있는데, 이때의 주요 가정 가운데 하나는 이미지의 중앙 영역의 중요성에 관련된 것이었다. 이것은 이미지의 중앙 영역에 의미 있는 객체가 위치할 가능성이 높다는 관찰로부터 기인한 것으로, 본 연구에서는 이러한 관찰 결과가 객관적으로 타당할 것인가를 S.K. Chang의 PIM(Picture Information Measure) 엔트로피를 계산하여 검증하려 하였다. 실험 결과 이미지의 중앙과 그 외부 영역 사이에는 통계적으로 유의미한 차이가 존재하는 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• Journal of applied mathematics & informatics
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• 제26권3_4호
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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.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (C)
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• pp.218-221
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• 2006

본 논문은 인터넷의 대표적인 문제점중의 하나인 Adult Image 분류 연구에 대해 기술한다. 특히 우리는 이러한 Adult Image를 분류하기 위한 Data Set을 5가지 타입으로 구성한다. 이러한 각 Image에 대해 Color, Gradient, Edge Direction 특성의 Feature들을 추출하고 이를 Histogram으로 구성한다. 이렇게 구성된 Histogram을 Support Vector Machine에 적용하여 Adult Image를 분류한다. 그 결과, 우리는 8250개의 Test Set에 대하여 Recall(96.53%), Precision(97.33%), False Positive(2.96%), F-Measure(96.93%)의 성능 결과를 보여준다.

• 한국통신학회논문지
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• 제21권4호
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• pp.848-854
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• 1996

Many image display devices allow only a limited number of colors to be simultaneously displayed. in disphaying of natural color image using color palette, it is necessary to construct an optimal color palette and the optimal mapping of each pixed of the original image to a color from the palette. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. The same as the clustering process, original color value. The proposed algorithm incroporated with a spatial activity weighting value which is reflected sensitivity of HVS quantization errors in smoothing region. This method produces high quality display images and considerably reduces computation time.

• Journal of Ubiquitous Convergence Technology
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• 제2권1호
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• pp.27-39
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• 2008

In this paper we present a simple, efficient method for detecting the blurry photographs. Recently many digital cameras are equipped with various auto-focusing functions to help users take well-focused pictures as easily as possible. In addition, motion compensation devices are able to compensate motion causing blurriness in the images. However, digital pictures can be degraded by limited contrast, inappropriate exposure, imperfection of auto-focusing or motion compensating devices, unskillfulness of the photographers, and so on. In order to decide whether to process the images or not, or whether to delete them or not, reliable measure of image degradation to detect blurry images from sharp ones is needed. This paper presents a blurriness/sharpness measure, and demonstrates its feasibility by using extensive experiments. This method is fast, easy to implement and accurate. Regardless of the detection accuracy, the proposed measure in this paper is not demanding in computation time. Needless to say, this measure can be used for various imaging applications including auto-focusing and astigmatism correction.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2005년도 추계종합학술대회
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• pp.327-331
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• 2005

본 논문에서는 영상에 대한 선명도를 측정하기 위한 또 다른 방법을 제시하였으며 기존의 필터링을 통한 이미지 선명화 측정과 달리 간단한 히스토그램을 가지고 수식으로 유도해 보았다. 히스토그램의 많은 정보 중에 다이나믹 레인지와 gray level, 각 level의 정도 곡선이 사용 되었으며 log scale로 그 범위를 한정 시켜 주었다. 그 결과 어느 정도 타당한 결과 값이 나왔으며, 이 결과를 토대로 HP, LP에 의한 필터링 방법 외에 또 다른 방법의 가능성을 제시한다.Q

• International journal of advanced smart convergence
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• 제11권3호
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• pp.179-186
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• 2022

In this paper, we design a heart rate measurement system using a web camera. In order to measure the heart rate, face image information is acquired and classified. The face image data is collected from web camera. The heart rate is measured using the collected face image data. We design a function to measure heart rate using input of face information using a web camera in non-contact manner. We design a function that reads face information and estimates heart rate by analyzing face color. An experiment was performed to compare the non-contact heart rate with the actual measured heart rate. The heart rate measurement system using a web camera proposed in this paper is a technology that can be used in various fields. It will be used in sports fields that require heart rate measurement at a low cost.