• Title/Summary/Keyword: Haar-like

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Robust Detection of Body Areas Using an Adaboost Algorithm (에이다부스트 알고리즘을 이용한 인체 영역의 강인한 검출)

  • Jang, Seok-Woo;Byun, Siwoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.11
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    • pp.403-409
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    • 2016
  • Recently, harmful content (such as images and photos of nudes) has been widely distributed. Therefore, there have been various studies to detect and filter out such harmful image content. In this paper, we propose a new method using Haar-like features and an AdaBoost algorithm for robustly extracting navel areas in a color image. The suggested algorithm first detects the human nipples through color information, and obtains candidate navel areas with positional information from the extracted nipple areas. The method then selects real navel regions based on filtering using Haar-like features and an AdaBoost algorithm. Experimental results show that the suggested algorithm detects navel areas in color images 1.6 percent more robustly than an existing method. We expect that the suggested navel detection algorithm will be usefully utilized in many application areas related to 2D or 3D harmful content detection and filtering.

Lower Tail Light Learning-based Forward Vehicle Detection System Irrelevant to the Vehicle Types (후미등 하단 학습기반의 차종에 무관한 전방 차량 검출 시스템)

  • Ki, Minsong;Kwak, Sooyeong;Byun, Hyeran
    • Journal of Broadcast Engineering
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    • v.21 no.4
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    • pp.609-620
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    • 2016
  • Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.

The Implementation of Automatic Compensation Modules for Digital Camera Image by Recognition of the Eye State (눈의 상태 인식을 이용한 디지털 카메라 영상 자동 보정 모듈의 구현)

  • Jeon, Young-Joon;Shin, Hong-Seob;Kim, Jin-Il
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.3
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    • pp.162-168
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    • 2013
  • This paper examines the implementation of automatic compensation modules for digital camera image when a person is closing his/her eyes. The modules detect the face and eye region and then recognize the eye state. If the image is taken when a person is closing his/her eyes, the function corrects the eye and produces the image by using the most satisfactory image of the eye state among the past frames stored in the buffer. In order to recognize the face and eye precisely, the pre-process of image correction is carried out using SURF algorithm and Homography method. For the detection of face and eye region, Haar-like feature algorithm is used. To decide whether the eye is open or not, similarity comparison method is used along with template matching of the eye region. The modules are tested in various facial environments and confirmed to effectively correct the images containing faces.

Efficient Face Detection based on Skin Color Model (피부색 모델 기반의 효과적인 얼굴 검출 연구)

  • Baek, Young-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.6
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    • pp.38-43
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    • 2008
  • Skin color information is an important feature for face region detection in color images. This can detect face region using statistical skin color model who is created from skin color information. However, due to the including of different race of people's skin color points, this general statistical model is not accurate enough to detect each specific image as we expected. This paper proposes method to detect correctly face region in various color image that other complexion part is included. In this method set face candidate region applying complexion Gausian distribution based on YCbCr skin color model and applied mathematical morphology to remove noise part and part except face region in color image. And achieved correct face region detection because using Haar-like feature. This approach is capable to distinguish face region from extremely similar skin colors, such as neck skin color or am skin color. Experimental results show that our method can effectively improve face detection results.

Face Recognition System for Unattended reception interface (무인 접수 인터페이스를 위한 얼굴인식 시스템)

  • Park, Se-Hyun;Ryu, Jeong-Tak
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.3
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    • pp.1-7
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    • 2012
  • As personal information is utilized as an important user authentication means, a trustable certification means is being required. Recently, a research on the biometrics system using a part of the human body like a password is being attempted a lot. The face recognition technology using characteristics of the personal face among several biometrics technologies is easy in extracting features. In this paper, we implement a face recognition system for unattended reception interface. Our method is performed by two steps. Firstly the face is extracted using Haar-like feature method. Secondly the method combining PCA and LDA for face recognition was used. To assess the effectiveness of the proposed system, it was tested and experimental results show that the proposed method is applicable for unattended reception interface.

Real-Time Pupil Detection System Using PC Camera (PC 카메라를 이용한 실시간 동공 검출)

  • 조상규;황치규;황재정
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.8C
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    • pp.1184-1192
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    • 2004
  • A real-time pupil detection system that detects the pupil movement from the real-time video data achieved by the visual light camera for general purpose personal computer is proposed. It is implemented with three steps; at first, face region is detected using the Haar-like feature detection scheme, and then eye region is detected within the face region using the template-based scheme. Finally, pupil movement is detected within the eye region by convolution of the horizontal and vertical histogram profiling and Gaussian filter. As results, we obtained more than 90% of the detection rate from 2375 simulation images and the data processing time is about 160㎳, that detects 7 times per second.

Detection Method of Face Rotation Angle for Crosstalk Cancellation (크로스토크 제거를 위한 얼굴 방위각 검출 기법)

  • Han, Sang-Il;Cha, Hyung-Tai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.58-65
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    • 2007
  • The method of 3D sound realization using 2 speakers provides two advantages: cheap and easy to build. In the case, crosstalk between 2 speakers has to be eliminated. To calculate and remove the effect of the crosstalk it is essential to find a rotation angle of human head correctly. In the paper, we suggest an algorithm to find the head angle of 2 channel system. We first detect a face area of the given image using Haar-like feature. After that, the eve detection using pre-processor and morphology method. Finally, we calculate the face rotation angle with the face andi the eye location. As a result of the experiment on various face images, the proposed method improves the efficiency much better than the conventional methods.

Vision based Traffic Light Detection and Recognition Methods for Daytime LED Traffic Light (비전 기반 주간 LED 교통 신호등 인식 및 신호등 패턴 판단에 관한 연구)

  • Kim, Hyun-Koo;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.3
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    • pp.145-150
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    • 2014
  • This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

A Study on Utilizing Smartphone for CMT Object Tracking Method Adapting Face Detection (얼굴 탐지를 적용한 CMT 객체 추적 기법의 스마트폰 활용 연구)

  • Lee, Sang Gu
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.588-594
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    • 2021
  • Due to the recent proliferation of video contents, previous contents expressed as the character or the picture are being replaced to video and growth of video contents is being boosted because of emerging new platforms. As this accelerated growth has a great impact on the process of universalization of technology for ordinary people, video production and editing technologies that were classified as expert's areas can be easily accessed and used from ordinary people. Due to the development of these technologies, tasks like that recording and adjusting that depends on human's manual involvement could be automated through object tracking technology. Also, the process for situating the object in the center of the screen after finding the object to record could have been automated. Because the task of setting the object to be tracked is still remaining as human's responsibility, the delay or mistake can be made in the process of setting the object which has to be tracked through a human. Therefore, we propose a novel object tracking technique of CMT combining the face detection technique utilizing Haar cascade classifier. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the smartphone in real time.