• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.43-48
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• 2000

중간 및 하부 대규권의 열적 상태에 대한 결과들의 상대적인 정확성을 평가하기 위하여 대기대순환 모델의 재분석(1980-93년) 그리고 세 종류의 위성관측 자료들(1980-97년)을 태평양, 한반도 부근에 대한 시.공간 분석으로 상호 비교하였다. 중간 대류권 온도를 반영하는 위성자료는 본 연구에서 유도된 Microwave Sounding Unit (MSU) 채널2 직하점 밝기온도(MSU2)와 Spencer and Christy(1992a)가 전체 주사자료를 사용하여 유도된 채널2 밝기 온도(SC2)이고, 하부 대류권 온도를 반영하는 위성자료는 Spencer and Christy(1992a)가 유도한 것이다(SC2R). 또한, 모델 자료는 ECMWF 재분석 온도이며, 위성관측 자료와의 비교를 위하여 재구성되었다. 한편, 각 위.경도 격자에서 위성관측과 모델 재분석의 월평균 값들의 상관도 전구적으로 조사하였다. 세 종류의 관측 자료들 간의 상관은 중.고위도에서 높았으나(r$\geq$0.9), 저위도 그리고 대류가 활발한 열대 서태평양 및 콩고강 부근에서 낮았다(r~0.65). 특히 SC2R에 대한 다른 자료의 상관이 상대적으로 낮았다. 이는 하부 대류권의 열적 상태를 반영하는 SC2R이 수적 및 지표방출의 영향으로 잡음을 크게 내포하기 때문인 것으로 추정되었다. 관측들과 모델 온도에 대한 월평균과 아노말리 값의 분석에서 시.공간 변동은 대체로 유사하였다. 관측 및 모델 자료는 열대 태평양 이외의 지역에 대한 월평균 값 모드1에서 연주기를 보였으나, 열대 태평양의 경우 모드2에서 보였다. 열대 태평양의 MSU2 모드1은 Walker 순환에 의한 동.서 대비를 보인 반면, 다른 위성관측과 모델 자료에서는 이러한 형태가 현저하지 않았다. 이 지역의 아노말리 값 모드2에서 위성관측들은 엘리뇨 기간에 적도를 중심으로 열대 동태평양 부근에서 아령모양의 대칭 형태를 보였으나 모델 결과에서는 이러한 특징이 약하였다. 관측과 모델 모두는 열대 태평양에 대한 아노말리 값의 모드 1,2에서 엘니뇨와 라니냐에 의한 경년변동을 뚜렷하게 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1428-1434
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• 2018

Canine cataract is developed with aging and can cause the blindness or surgical treatment if not treated timely. In this paper, we propose a method for extracting cataract suspicious areas automatically with FCM(Fuzzy C_Means) algorithm to overcome the weakness of previously attempted ART2 based method. The proposed method applies the fuzzy stretching technique and the Max-Min based average binarization technique to the dog eye images photographed by simple devices such as mobile phones. After applying the FCM algorithm in quantization, we apply the brightness average binarization method in the quantized region. The two binarization images - Max-Min basis and brightness average binarization - are ANDed, and small noises are removed to extract the final cataract suspicious areas. In the experiment with 45 dog eye images with canine cataract, the proposed method shows better performance in correct extraction rate than the ART2 based method.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.21-30
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• 2009

The purposes of this paper are to present a selection method of neighboring pixels whose local statistics are similar to the center pixel and combine the selection result with mean curvature diffusion filter to reduce noises in remote sensed imagery. The order of selection of neighboring pixels is critical, especially for finding a pixel belonging to the homogeneous region, since the statistics of the homogeneous region vary according to the selection order. An effective strategy for selecting neighboring pixels, which uses rank-order differences vector obtained by computing the intensity differences between the center pixel and neighboring pixels and arranging them in ascending order, is proposed in this paper. By using region growing method, we divide the elements of the rank-ordered differences vector into two groups, homogeneous rank-ordered differences vector and outlier rank-ordered differences vector. The mean curvature diffusion filter is combined with a line process, which chooses selectively diffusion coefficient of the neighboring pixels belonging into homogeneous rank-ordered differences vector. Experimental results using an aerial image and a TerraSAR-X satellite image showed that the proposed method reduced more efficiently noises than some conventional adaptive filters using all neighboring pixels in updating the center pixel.

• Annual Conference of KIPS
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• 2002.11a
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• pp.629-632
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• 2002

본 논문에서는 획득 영상에서 k-평균 알고리즘에 의한 무게중심을 이용하여 이동 물체를 검출하고 추적하는 방법을 제안하였다. 이동 물체의 검출은 획득 영상에 대하여 차영상 후 에지 검출에 의해 수행된다. 제안한 검출 방법은 빛의 밝기와 각도에 의해 발생된 그림자 등의 변형을 제거하고, 이동 물체만을 검출할 수 있어, 빛에 영향을 받은 영상에 대해서도 이동 물체를 양호하게 검출할 수 있다. 물체 추적은 검출된 이동 물체에 대하여 k-평균 알고리즘으로 세 개의 물체 무게중심을 구하고, 무게중심 부근의 화소 평균값과 무게중심간의 거리를 구한다. 다음 프레임들에 대하여 탐색영역의 화소 평균값에 의해 후보 무게중심을 구하고, 물체 무게중심과 구한 후보 무게중심들의 표준편차와 무게중심간의 거리 차를 이용하여 이동 물체를 추적한다. 그 결과, 이동 물체의 추적 속도를 개선시켰고, 물체 추적 오차율을 줄였다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.458-462
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• 2010

본 논문은 X-선 혈관조영영상에서 기울기 정보 및 최대 빈도수를 이용한 카테터 자동 분할 방법을 제안한다. 제안방법은 세 단계로 이루어진다. 첫째, 분할하고자 하는 카테터 관심영역을 설정하고, 영상의 대조대비를 높이기 위한 밝기값 스트레칭을 수행한다. 둘째, 카테터 후보 경계점을 추출하기 위하여 카테터 방향을 고려한 경계 강조 마스크를 영상에 적용한다. 셋째, 카테터 후보 경계점에서 기울기가 크고 최대 빈도수 직경을 갖는 카테터 경계점을 추출하고 이들을 선형 보간하여 최종 카테터 경계를 분할한다. 제안 방법의 평가를 위하여 육안 평가 및 전문가가 수동 분할한 결과와 본 제안방법을 적용하여 얻은 중복 영역 비율과 평균 거리 차이를 측정한 정확성 평가를 수행하였고, 수행시간을 측정하였다. 실험결과 중복 영역 비율은 93.9%${\pm}$2.7%, 평균 거리 차이는 0.116-픽셀, 수행시간은 평균 0.011초로 측정되었다.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.305-322
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• 2005

Watermarking is a widely employed method tn protecting copyright of a digital image, the owner's unique image is embedded into the original image. Strengthened level of watermark insertion would help enhance its resilience in the process of extraction even from various distortions of transformation on the image size or resolution. However, its level, at the same time, should be moderated enough not to reach human visibility. Finding a balance between these two is crucial in watermarking. For the algorithm for watermarking, the predefined strength of a watermark, computed from the physical difference between the original and embedded images, is applied to all images uniformal. The mean brightness or contrast of the surrounding images, other than the absolute brightness of an object, could affect human sensitivity for object detection. In the present study, we examined whether the detectability for watermark noise might be attired by image statistics: mean brightness and contrast of the image. As the first step to examine their effect, we made rune fundamental images with varied brightness and control of the original image. For each fundamental image, detectability for watermark noise was measured. The results showed that the strength ot watermark node for detection increased as tile brightness and contrast of the fundamental image were increased. We have fitted the data to a regression line which can be used to estimate the strength of watermark of a given image with a certain brightness and contrast. Although we need to take other required factors into consideration in directly applying this formula to actual watermarking algorithm, an adaptive watermarking algorithm could be built on this formula with image statistics, such as brightness and contrast.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.110-119
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• 2010

In this paper, we propose an automatic segmentation of the prostate using intensity distribution and gradient information in MR images. First, active shape model using adaptive intensity profile and multi-resolution technique is used to extract the prostate surface. Second, hole elimination using geometric information is performed to prevent the hole from occurring by converging the surface shape to the local optima. Third, the surface shape with large anatomical variation is corrected by using 2D gradient information. In this case, the corrected surface shape is often represented as rugged shape which is generated by the limited number of vertices. Thus, it is reconstructed by using surface modelling and smoothing. To evaluate our method, we performed the visual inspection, accuracy measures and processing time. For accuracy evaluation, the average distance difference and the overlapping volume ratio between automatic segmentation and manual segmentation by two radiologists are calculated. Experimental results show that the average distance difference was 0.3${\pm}$0.21mm and the overlapping volume ratio was 96.31${\pm}$2.71%. The total processing time of twenty patient data was 16 seconds on average.

• Convergence Security Journal
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• v.13 no.3
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• pp.9-15
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• 2013

Calculating of matching cost is an important for efficient stereo matching. To investigate the performance of matching process, the concepts of the existing methods are introduced. Also we analyze the performance and merits of them. The simplest matching costs assume constant intensities at matching image locations. We consider matching cost functions which can be distinguished between pixel-based and window-based approaches. The Pixel-based approach includes absolute differences (AD) and sampling-intensitive absolute differences (BT). The window-based approach includes the sum of the absolute differences, the sum of squared differences, the normalized cross-correlation, zero-mean normalized cross-correlation, census transform, and the absolute differences census transform (AD-Census). We evaluate matching cost functions in terms of accuracy and time complexity. In terms of the accuracy, AD-Census method shows the lowest matching error ratio (the best solution). The ZNCC method shows the lowest matching error ratio in non-occlusion and all evaluation part. But it performs high matching error ratio at the discontinuities evaluation part due to blurring effect in the boundary. The pixel-based AD method shows a low complexity in terms of time complexity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.89-90
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• 2010

기존의 HDR (high dynamic range) 영상취득 기법은 한 장의 HDR 영상을 얻기 위해 여러 장의 LDR (low dynamic range) 영상을 취득하기 때문에 영상 취득에 많은 시간이 소요된다. 본 논문에서는 이런 단점을 보안하기 위해 두 장의 LDR 영상을 이용하여 평균 밝기 값에 대한 노출 곡선을 추정한다. 그리고 추정된 노출곡선을 이용하여 밝은 영상과 어두운 영상 각각의 최적의 노출 시간을 취득하는 기법을 제안한다.