• Smart Media Journal
• /
• v.5 no.1
• /
• pp.38-43
• /
• 2016

As smart environment is spread out in our living environments, the needs of an approach related to Human Computer Interaction(HCI) is increases. One of them is head pose estimation. it related to gaze direction estimation, since head has a close relationship to eyes by the body structure. It's a key factor in identifying person's intention or the target of interest, hence it is an essential research in HCI. In this paper, we propose an approach for head pose estimation with pre-defined several directions by random forest classifier. We use canny edge detector to extract feature of the different facial image which is obtained between input image and averaged frontal facial image for extraction of rotation information of input image. From that, we obtain the binary edge image, and make two accumulated histograms which are obtained by counting the number of pixel which has non-zero value along each of the axes. This two accumulated histograms are used to feature of the facial image. We use CAS-PEAL-R1 Dataset for training and testing to random forest classifier, and obtained 80.6% accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.138-139
• /
• 2012

본 논문에서는 보다 정밀한 깊이 정보를 추출하기 위하여, 밝기 차이에 강인한 스테레오 정합 기법을 개발한다. 우선 촬영된 환경에 따라 발생하는 스테레오 영상의 노출 차이를 보상하기 위하여, 전체 영상에 대하여 전역적으로 히스토그램 기반의 3 차원 누적 분포 함수를 계산한다. 계산된 3 차원 누적 분포 함수를 기반으로 순위 영상을 생성하고, 밝기 기반의 강인한 초기 정합을 수행한다. 다음으로 지역적인 밝기 변화에 강인하도록, 초기 깊이 정보를 바탕으로 EM 알고리즘을 수행하여 객체와 배경에 해당되는 깊이 정보를 분리한다. 분리된 영역 정보를 기반으로 각각의 영역의 대하여 다시 히스토그램 기반의 3 차원 누적 분포 함수를 계산한다. 이를 기반으로 최종적으로 전경과 배경의 차등적인 정합을 수행하여 지역적인 밝기 차이에 강인한 스테레오 정합기법을 개발한다. 다양한 실험을 통하여 본 논문에서 제안하는 기법의 성능을 확인한다.

• Journal of KIISE:Software and Applications
• /
• v.31 no.5
• /
• pp.605-616
• /
• 2004

A new practical implementation of a facial verification system using cumulative histogram of surface curvatures for the local and contour line areas is proposed, in this paper. The approach works by finding the nose tip that has a protrusion shape on the face. In feature recognition of 3D face images, one has to take into consideration the orientated frontal posture to normalize after extracting face area from the original image. The feature vectors are extracted by using the cumulative histogram which is calculated from the curvature of surface for the contour line areas: 20, 30 and 40, and nose, mouth and eyes regions, which has depth and surface characteristic information. The L1 measure for comparing two feature vectors were used, because it was simple and robust. In the experimental results, the maximum curvature achieved recognition rate of 96% among the proposed methods.

• Journal of the Korea Convergence Society
• /
• v.10 no.3
• /
• pp.15-22
• /
• 2019

In this paper, we proposed a Hangeul detection method using structural features of histogram, consonant, and vowel to solve the problem of Hangul which is separated and detected consonant and vowel The proposed method removes background by using DoG (Difference of Gaussian) to remove unnecessary noise in Hangul detection process. In the image with the background removed, we converted it to a binarized image using a cumulative histogram. Then, the horizontal position histogram was used to find the position of the character string, and character combination was performed using the vertical histogram in the found character image. However, words with a consonant vowel such as '가', '라' and '귀' are combined using a structural characteristic of characters because they are difficult to combine into one character. In this experiment, an image composed of alphabets with various backgrounds, an image composed of Korean characters, and an image mixed with alphabets and Hangul were tested. The detection rate of the proposed method is about 2% lower than that of the K-means and MSER character detection method, but it is about 5% higher than that of the character detection method including Hangul.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.2
• /
• pp.21-28
• /
• 2008

This paper proposes a novel reduced-reference assessment method for video quality assessment, in which one-dimensional (1-D) histograms of motion vectors (MVs) are used as features of videos. The proposed method is more efficient than the conventional methods in view of computation time, because the proposed quality metric decodes MVs directly from video stream in the parsing process instead of reconstructing the distorted video at the receiver. Moreover, in view of data size, the propose method is efficient because a sender transmits 1-D histograms of MVs accumulated over whole input video sequences. Here, we use 1-D histograms of MVs accumulated over the whole video sequences, which is different from the conventional methods that assessed each image independently. For testing the similarity between histograms, we use histogram intersection and histogram difference methods. We compare the proposed method with the conventional methods for 52 video clips, which are coded under varying bit rate, image size, and frame rate. Experimental results show that the proposed method is more efficient than the conventional methods and that the proposed method is more similar to the mean opinion score (MOS) than conventional algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.11a
• /
• pp.191-194
• /
• 2009

본 논문에서는 효율적인 다시점 비디오 부호화를 위해 히스토그램(histogram)을 이용한 다시점 비디오의 휘도(luminance)와 색차(chrominance)성분 보상 기법을 제안한다. 다시점 비디오는 카메라의 기하학적인 위치 차이와 여러 대의 카메라가 동일한 특성을 가지도록 완벽히 조정되지 못함으로 인해 동일한 시간대에 촬영된 인접한 시점 영상 간에 휘도와 색상의 차이가 발생할 수 있다. 이러한 특성은 인접한 카메라로부터 획득된 영상을 참조하여 시점간 움직임 예측 시에 오정합의 원인이 되어 부호화 효율을 떨어뜨리게 된다. 본 논문에서는 효율적인 다시점 비디오 부호화를 위해 시점간의 히스토그램을 비교하여 정합하는 휘도 및 색차 보상 기법을 수행한다. 일정한 시간 대역(time interval)에서 다시점 비디오의 평균 누적 히스토그램을 이용하여 참조 영상을 생성하고 각 시점별로 정합 함수를 통해 다시점 영상 간의 휘도와 색상의 불일치성을 보상한다. 제안하는 조명 보상 기법을 통하여 다시점 비디오 부호화 효율을 높일 수 있었다.

• The KIPS Transactions:PartB
• /
• v.11B no.7 s.96
• /
• pp.779-784
• /
• 2004

In this paper, we have proposed an image contrast control method using brightness preserving on the FPD(Flat Panel Display). The proposed method can be easily applied to the FPD required real-time processing, since hardware complexity is greatly reduced using linear approximation method of CDF(Cumulative Density Function). For effective processing of the proposed algorithm, we have utilized the sample value of CDF and Barrel Shift. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of the pro-posed method and the original ones.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.11a
• /
• pp.579-582
• /
• 2003

본 논문에서는 동영상에서 에지 정보와 히스토그램 분석을 이용하여 실시간으로 움직이는 물체를 검출하고 추적하는 방법을 제안하였다. 물체 검출에서는 먼저, 입력영상에 대하여 형태에 관한 정보를 그대로 유지하면서 자료의 양을 줄일 수 있는 에지(Edge)를 추출한다. 추출된 에지 영상에 차연산과 이진화를 수행하여 물체를 검출하고, 검출된 물체 영역은 이진 변환밀도에 대한 수평 누적값의 합을 수평 수직 최대 누적값을 더한 값으로 나눈 임계값으로 구한다. 물체 추적에서는 현재 프레임에서 검출된 물체와 이전 프레임에서 검출된 물체와의 유사성을 비교하여 추적한다. 실험결과 물체 검출속도를 개선시켰고, 실시간으로 물체를 추적할 수 있었으며, 국부적인 움직임까지도 추적할 수 있었다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.7
• /
• pp.4475-4481
• /
• 2014

A histogram equalization method have been used traditionally for the image enhancement of low quality images. This uses the transformation function, which is a cumulative density function of an input image, and it has mathematically maximum entropy. This method, however, may yield whitening artifacts. This paper proposes the weighted histogram equalization method based on histogram equalization. It has Weber-Fechner's law for a human's vision characteristics, and a dynamic range modification to solve the problem of some methods, which yield a transformation function, regardless of the input image. Finally, the proposed transformation function was calculated using the weighted average of Weber-Fechner and the histogram equalization transformation functions in a modified dynamic range. The simulation results showed that the proposed algorithm effectively enhances the contrast in terms of the subjective quality. In addition, the proposed method has similar or higher entropy than the other conventional approaches.

• Journal of Environmental Impact Assessment
• /
• v.29 no.1
• /
• pp.37-44
• /
• 2020

In this study, we analyzed the value of Chl-a by histogram to classify the points where algal management is required. The degree of algal bloom by point was analyzed using the ogive curve, and the algal control points were classified into three stages according to the shape of the frequency distribution table. Of the four major rivers, low concentration of Chl-a appeared most frequently in the Han River, while the high concentration of Chl-a was frequently found at the points of the Geum and the Yeongsan Rivers. In the case of the Han River, no apprehensive areas were found thatrequire intensive management, while most points on the Geum and the Yeongsan Rivers required algal management. Finally, the Nakdong River basin was identified as points requiring algal management from the mid to downstream. The results of this study have confirmation of the possibility that the frequency distribution could be used as a supplementary indicator to express the algal bloom.