• 제목/요약/키워드: histogram of oriented gradients

검색결과 48건 처리시간 0.032초

Two-wheeler Detection System using Histogram of Oriented Gradients based on Local Correlation Coefficients and Curvature

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • 제2권4호
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    • pp.303-310
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    • 2015
  • Vulnerable road users such as bike, motorcycle, small automobiles, and etc. are easily attacked or threatened with bigger vehicles than them. So this paper suggests a new approach two-wheelers detection system riding on people based on modified histogram of oriented gradients (HOGs) which is weighted by curvature and local correlation coefficient. This correlation coefficient between two variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using the curvature of Gaussian and Histogram of Oriented Gradients (HOG) which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the correlation coefficient between the area of each cell and one of bike, can be used as the weighting factor in process for normalizing the HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. The experimental results validate the effectiveness of our proposed algorithm show higher than that of the traditional method and under challenging, such as various two-wheeler postures, complex background, and even conclusion.

Title Extraction from Book Cover Images Using Histogram of Oriented Gradients and Color Information

  • Do, Yen;Kim, Soo Hyung;Na, In Seop
    • International Journal of Contents
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    • 제8권4호
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    • pp.95-102
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    • 2012
  • In this paper, we present a technique to extract the title areas from book cover images. A typical book cover image may contain text, pictures, diagrams as well as complex and irregular background. In addition, the high variability of character features such as thickness, font, position, background and tilt of the text also makes the text extraction task more complicated. Therefore, we propose a two steps efficient method that uses Histogram of Oriented Gradients and color information to find the title areas. Firstly, text localization is carried out to find the title candidates. Finally, refinement process is performed to find the sufficient components of title areas. To obtain the best result, we also use other constraints about the size, ratio between the length and width of the title. We achieve encouraging results of extracted title regions from book cover images which prove the advantages and efficiency of the proposed method.

An Object Classification Algorithm Based on Histogram of Oriented Gradients and Multiclass AdaBoost

  • Yun, Anastasiya;Lenskiy, Artem;Lee, Jong Soo
    • 한국정보전자통신기술학회논문지
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    • 제1권3호
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    • pp.83-89
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    • 2008
  • This paper introduces a visual object classification algorithm based on statistical information. Objects are characterized through the Histogram of Oriented Gradients (HOG) method and classification is performed using Multiclass AdaBoost. Salient features of an object's appearance are detected by HOG blocks Blocks of different sizes are tested to define the most suitable configuration. To select the most informative blocks for classification a multiclass AdaBoostSVM algorithm is applied. The proposed method has a high speed processing and classification rate. Results of the evaluation based on example of hand gesture recognition are presented.

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군복의 색깔을 이용한 피아식별 기법 (IFF Technique using the Color of Military Uniform)

  • 허우형;구은진;차의영
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2013년도 제47차 동계학술대회논문집 21권1호
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    • pp.23-25
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    • 2013
  • 본 논문에서는 차세대 무인 군사 로봇에 활용할 수 있는 적군 및 아군 식별 수단으로 군복의 색깔을 이용한 기법을 제안한다. 이 기법은 전장지역의 군사로봇이 할 수 있는 피아식별법 중에 하나로 로봇에 부착되어 있는 카메라 외에 추가적으로 가져야 하는 장비가 필요 없기 때문에 추가비용 없이 효과적으로 적군을 포착할 수 있다. 군복의 색깔 차이를 식별하기 위해서는 먼저 HOG(Histogram of Oriented Gradients) 기법을 이용하여 사람을 검출한 다음, 이후 검출된 사람영역에 대하여 인체 비율을 고려해서 추출한 상의 부분의 색깔 데이터를 받는다. 이때 색공간은 HSV 공간으로 하여 조명의 변화에 덜 민감하도록 하였다. 북한 군복 색깔 영역의 pixel들만 추출하여 이진화를 한 후, 상의 전체 픽셀에 대한 개수 비율을 계산한다. 비율이 임계값 보다 높을 경우 적으로 인식한다.

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New approach to two wheelers detection using Cell Comparison

  • Lee, Yeunghak;Kim, Taesun;Lee, Sanghoon;Shim, Jaechang
    • Journal of Multimedia Information System
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    • 제1권1호
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    • pp.45-53
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    • 2014
  • This article describes a two wheelers detection system riding on people based on modified histogram of oriented gradients (HOG) for vision based intelligent vehicles. These features used correlation coefficient parameter are able to classify variable and complicated shapes of a two wheelers according to different viewpoints as well as human appearance. Also our system maintains the simplicity of evaluation of traditional formulation while being more discriminative. In this paper, we propose an evolutionary method trained part-based models to classify multiple view-based detection: frontal, rear and side view (within $60^{\circ}C$). Our experimental results show that a two wheelers riding on people detection system based on proposed approach leads to higher detection accuracy rate than traditional features.

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영상 내 사람의 검출을 위한 에지 기반 방법 (Edge-based Method for Human Detection in an Image)

  • 도용태;반종희
    • 센서학회지
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    • 제25권4호
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    • pp.285-290
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    • 2016
  • Human sensing is an important but challenging technology. Unlike other methods for sensing humans, a vision sensor has many advantages, and there has been active research in automatic human detection in camera images. The combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is currently one of the most successful methods in vision-based human detection. However, extracting HOG features from an image is computer intensive, and it is thus hard to employ the HOG method in real-time processing applications. This paper describes an efficient solution to this speed problem of the HOG method. Our method obtains edge information of an image and finds candidate regions where humans very likely exist based on the distribution pattern of the detected edge points. The HOG features are then extracted only from the candidate image regions. Since complex HOG processing is adaptively done by the guidance of the simpler edge detection step, human detection can be performed quickly. Experimental results show that the proposed method is effective in various images.

HOG를 이용한 다중객체 검출과 효과적인 개별객체 추적 (Multi-objects detection using HOG and effective individual object tracking)

  • 최민;이규원
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2012년도 추계학술대회
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    • pp.894-897
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    • 2012
  • HOG(Histogram of Oriented Gradients)의 특징벡터를 이용하여 여러 객체가 움직이는 환경에서의 효과적인 개별객체 추적 방법을 제안한다. 알고리즘의 구성은 크게 영상의 전처리 과정, 객체검출, 객체추적으로 구성하였고, 다양한 궤적과 객체의 움직임을 갖는 6개의 동영상을 이용하여 실험하였다. 객체간에 겹치는 현상이 일어났을 때, 객체의 중심좌표와 예측좌표를 이용하여 개별 객체를 구분하였다. 제안한 시스템을 실험에 사용한 비디오에 적용한 결과 85.45%의 추적 성공률을 보였다. 제안한 시스템은 사물의 위치 및 움직임 패턴을 분석을 요하는 보안 시스템에 적용할 수 있을 것이다.

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국부적 Cell 히스토그램 시프트와 상관관계를 이용한 이륜차 인식 (Two-wheelers Detection using Local Cell Histogram Shift and Correlation)

  • 이상훈;이영학;김태선;심재창
    • 한국멀티미디어학회논문지
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    • 제17권12호
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    • pp.1418-1429
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    • 2014
  • In this paper we suggest a new two-wheelers detection algorithm using local cell features. The first, we propose new feature vector matrix extraction algorithm using the correlation two cells based on local cell histogram and shifting from the result of histogram of oriented gradients(HOG). The second, we applied new weighting values which are calculated by the modified histogram intersection showing the similarity of two cells. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

동영상에서 보행자 추적을 위한 변형된 HOG 특징 추출에 관한 연구 (Modified HOG Feature Extraction for Pedestrian Tracking)

  • 김회준;박영수;김기봉;이상훈
    • 한국융합학회논문지
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    • 제10권3호
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    • pp.39-47
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    • 2019
  • 본 논문에서는 실시간으로 보행자를 추적할 때 배경 제거를 이용하여 변형된 HOG(Histogram of Oriented Gradients) 특징 추출을 제안하였다. 기존의 HOG 특징 추출은 연산량이 많아 추적 속도가 느린 문제가 있다. 배경 제거를 통해 연산량 감소와 추적률을 향상시키기 위해 연구하였다. 불필요한 영역에서의 특징 추출을 감소시키기 위해 HSV 색공간에서 S 채널과 V 채널을 이용하여 영역 제거를 진행하였다. 영상의 평균 S 채널과 V 채널로 배경 제거 후 입력 영상이 전체적으로 어두워 객체 추적에 실패하는 경우가 있다. 이러한 경우를 방지하기 위해 히스토그램 평활화를 하였다. 제거된 영역에서 추출되는 HOG 특징이 감소되고, 객체에서는 명확한 HOG 특징이 추출되어 객체 추적 속도와 추적률이 향상되었다. 본 실험에서는 다수의 보행자나 한명의 보행자가 존재하는 영상, 배경이 복잡한 영상, 흔들림이 심한 영상을 가지고 실험하였다. 제안하는 방법은 기존의 HOG-SVM 방법과 비교하여 처리 속도는 약 41.84% 향상되었으며 오 추적률은 약 52.29% 감소되어 개선된 추적률을 보였다.

다문화 손동작 인식을 위한 HOG-HOD 알고리즘 (HOG-HOD Algorithm for Recognition of Multi-cultural Hand Gestures)

  • 김지예;박종일
    • 한국멀티미디어학회논문지
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    • 제20권8호
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    • pp.1187-1199
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    • 2017
  • In recent years, research about Natural User Interface (NUI) has become focused because NUI system can give natural feelings for users in virtual reality. Most important thing in NUI system is how to communicate with the computer system. There are many things to interact with users such as speech, hand gestures, body actions. Among them, hand gesture is suitable for the purpose of NUI because people often use a relatively high frequency in daily life and hand gesture have meaning only by itself. This hand gestures called multi-cultural hand gesture and we proposed the method to recognize this kind of hand gestures. Proposed method is composed of Histogram of Oriented Gradients (HOG) used for hand shape recognition and Histogram of Oriented Displacements (HOD) used for hand center point trajectory recognition.