• Title/Summary/Keyword: 특징점 추출 알고리즘

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Target Detection Using Texture Features and Neural Network in Infrared Images (적외선영상에서 질감 특징과 신경회로망을 이용한 표적탐지)

  • Sun, Sun-Gu
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.5
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    • pp.62-68
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    • 2010
  • This study is to identify target locations with low false alarms on thermal infrared images obtained from natural environment. The proposed method is different from the previous researches because it uses morphology filters for Gabor response images instead of an intensity image in initial detection stage. This method does not need precise extracting a target silhouette to distinguish true targets or clutters. It comprises three distinct stages. First, morphological operations and adaptive thresholding are applied to the summation image of four Gabor responses of an input image to find out salient regions. The locations of extracted regions can be classified into targets or clutters. Second, local texture features are computed from salient regions of an input image. Finally, the local texture features are compared with the training data to distinguish between true targets and clutters. The multi-layer perceptron having three layers is used as a classifier. The performance of the proposed method is proved by using natural infrared images. Therefore it can be applied to real automatic target detection systems.

Content-based Shot Boundary Detection from MPEG Data using Region Flow and Color Information (영역 흐름 및 칼라 정보를 이용한 MPEG 데이타의 내용 기반 셧 경계 검출)

  • Kang, Hang-Bong
    • Journal of KIISE:Software and Applications
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    • v.27 no.4
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    • pp.402-411
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    • 2000
  • It is an important step in video indexing and retrieval to detect shot boundaries on video data. Some approaches are proposed to detect shot changes by computing color histogram differences or the variances of DCT coefficients. However, these approaches do not consider the content or meaningful features in the image data which are useful in high level video processing. In particular, it is desirable to detect these features from compressed video data because this requires less processing overhead. In this paper, we propose a new method to detect shot boundaries from MPEG data using region flow and color information. First, we reconstruct DC images and compute region flow information and color histogram differences from HSV quantized images. Then, we compute the points at which region flow has discontinuities or color histogram differences are high. Finally, we decide those points as shot boundaries according to our proposed algorithm.

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Illumination-Robust Load Lane Color Recognition based on S-color Space (조명변화에 강인한 S-색상공간 기반의 차선색상 판별 방법)

  • Baek, Seung-Hae;Jin, Yan;Lee, Geun-Mo;Park, Soon-Yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.3
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    • pp.434-442
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    • 2018
  • In this paper, we propose a road lane color recognition method from the image obtained from a driving vehicle. In autonomous vehicle techniques, lane information becomes more important as the level of autonomous driving such as lane departure warning and dynamic lane keeping assistance is increased. In particular the lane color recognition, especially the white and the yellow lanes, is necessary technique because it is directly related to traffic accidents. In this paper, color information of lane and road area is mapped to a 2-dimensional S-color space based on lane detection. And the center of the feature distribution is obtained by using an improved mean-shift algorithm in the S-color space. The lane color is determined by using the distance between the center coordinates of the color features of the left and right lanes and the road area. In various illumination conditions, about 97% color recognition rate is achieved.

Stereo Vision Based 3D Input Device (스테레오 비전을 기반으로 한 3차원 입력 장치)

  • Yoon, Sang-Min;Kim, Ig-Jae;Ahn, Sang-Chul;Ko, Han-Seok;Kim, Hyoung-Gon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.4
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    • pp.429-441
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    • 2002
  • This paper concerns extracting 3D motion information from a 3D input device in real time focused to enabling effective human-computer interaction. In particular, we develop a novel algorithm for extracting 6 degrees-of-freedom motion information from a 3D input device by employing an epipolar geometry of stereo camera, color, motion, and structure information, free from requiring the aid of camera calibration object. To extract 3D motion, we first determine the epipolar geometry of stereo camera by computing the perspective projection matrix and perspective distortion matrix. We then incorporate the proposed Motion Adaptive Weighted Unmatched Pixel Count algorithm performing color transformation, unmatched pixel counting, discrete Kalman filtering, and principal component analysis. The extracted 3D motion information can be applied to controlling virtual objects or aiding the navigation device that controls the viewpoint of a user in virtual reality setting. Since the stereo vision-based 3D input device is wireless, it provides users with a means for more natural and efficient interface, thus effectively realizing a feeling of immersion.

Grading meat quality of Hanwoo based on SFTA and AdaBoost (SFTA와 AdaBoost 기반 한우의 육질 등급 분석)

  • Cho, Hyunhak;Kim, Eun Kyeong;Jang, Eunseok;Kim, Kwang Baek;Kim, Sungshin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.6
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    • pp.433-438
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    • 2016
  • This paper proposes a grade prediction method to measure meat quality in Hanwoo (Korean Native Cattle) using classification and feature extraction algorithms. The applied classification algorithm is an AdaBoost and the texture features of the given ultrasound images are extracted using SFTA. In this paper, as an initial phase, we selected ultrasound images of Hanwoo for verifying experimental results; however, we ultimately aimed to develop a diagnostic decision support system for human body scan using ultrasound images. The advantages of using ultrasound images of Hanwoo are: accurate grade prediction without butchery, optimizing shipping and feeding schedule and economic benefits. Researches on grade prediction using biometric data such as ultrasound images have been studied in countries like USA, Japan, and Korea. Studies have been based on accurate prediction method of different images obtained from different machines. However, the prediction accuracy is low. Therefore, we proposed a prediction method of meat quality. From the experimental results compared with that of the real grades, the experimental results demonstrated that the proposed method is superior to the other methods.

A Similarity Computation Algorithm for Music Retrieval System Based on Query By Humming (허밍 질의 기반 음악 검색 시스템의 유사도 계산 알고리즘)

  • Oh Dong-Yeol;Oh Hae-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.4 s.42
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    • pp.137-145
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    • 2006
  • A user remembers a melody as not the combination of pitch and duration which is written in score but the contour which is composed of the relative pitch and duration. Because of the way of remembering a melody the previous Music Information Retrieval Systems which uses keyboard Playing or score as the main input melody are not easily acceptable in Query By Humming Systems. In this paper, we mention about the considerable checkpoints for Query By Humming System and previous researches. And we propose the feature extraction which is similar with the way of remembering a melody and similarity computation algorithms between melody in humming and melody in music. The proposed similarity computation algorithms solves the problem which can be happened when only uses the relative pitches by using relative durations.

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Feature Vector Extraction and Classification Performance Comparison According to Various Settings of Classifiers for Fault Detection and Classification of Induction Motor (유도 전동기의 고장 검출 및 분류를 위한 특징 벡터 추출과 분류기의 다양한 설정에 따른 분류 성능 비교)

  • Kang, Myeong-Su;Nguyen, Thu-Ngoc;Kim, Yong-Min;Kim, Cheol-Hong;Kim, Jong-Myon
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.8
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    • pp.446-460
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    • 2011
  • The use of induction motors has been recently increasing with automation in aeronautical and automotive industries, and it playes a significant role. This has motivated that many researchers have studied on developing fault detection and classification systems of an induction motor in order to minimize economical damage caused by its fault. With this reason, this paper proposed feature vector extraction methods based on STE (short-time energy)+SVD (singular value decomposition) and DCT (discrete cosine transform)+SVD techniques to early detect and diagnose faults of induction motors, and classified faults of an induction motor into different types of them by using extracted features as inputs of BPNN (back propagation neural network) and multi-layer SVM (support vector machine). When BPNN and multi-lay SVM are used as classifiers for fault classification, there are many settings that affect classification performance: the number of input layers, the number of hidden layers and learning algorithms for BPNN, and standard deviation values of Gaussian radial basis function for multi-layer SVM. Therefore, this paper quantitatively simulated to find appropriate settings for those classifiers yielding higher classification performance than others.

Automatic 3D Object Digitizing and Its Accuracy Using Point Cloud Data (점군집 데이터에 의한 3차원 객체도화의 자동화와 정확도)

  • Yoo, Eun-Jin;Yun, Seong-Goo;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.1
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    • pp.1-10
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    • 2012
  • Recent spatial information technology has brought innovative improvement in both efficiency and accuracy. Especially, airborne LiDAR system(ALS) is one of the practical sensors to obtain 3D spatial information. Constructing reliable 3D spatial data infrastructure is world wide issue and most of the significant tasks involved with modeling manmade objects. This study aims to create a test data set for developing automatic building modeling methods by simulating point cloud data. The data simulates various roof types including gable, pyramid, dome, and combined polyhedron shapes. In this study, a robust bottom-up method to segment surface patches was proposed for generating building models automatically by determining model key points of the objects. The results show that building roofs composed of the segmented patches could be modeled by appropriate mathematical functions and the model key points. Thus, 3D digitizing man made objects could be automated for digital mapping purpose.

Similar Image Retrieval using Color Histogram and Edge Histogram Descriptor (컬러 히스토그램과 에지 히스토그램 디스크립터를 이용한 영상 검색 기법)

  • Jo, Min-Hyuk;Lee, Sang-Geol;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.332-335
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    • 2013
  • In this paper, we propose an image retrieval method using an EHD (Edge Histogram Descriptor) of MPEG-7 and the color histogram. The EHD algorithm can be used to collect the gradient of edge distribution and to find a similar image. However, if you only search the edge gradient without considering the image color, the color shows a weakness. In order to overcome this problem, we use the color histogram and extract the feature to determine whether a similar image. The proposed method shows that the weakness of existing EHD can be overcome by using the color histogram.

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Inspection of the Nuclear Fuel Rod Deformation using an Image Processing (영상처리를 이용한 핵연료봉의 변형 검사)

  • Cho, Jai-Wan;Choi, Young-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.1
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    • pp.91-96
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    • 2010
  • In this paper, a deformation measurement technology of the nuclear fuel rod is proposed. The deformation measurement system include high definition CCD or CMOS image sensor, lens, semiconductor laser line beam marker, and optical & mechanical accessories. The basic idea of the deformation measurement is to illuminate the outer surface of the fuel rod with collimated laser line beam at an angle of 45 degrees or higher. The relative motion of the fuel rod in the horizontal direction causes the illuminated laser line beam to move vertically along the surface of the fuel rod. The resulting change of laser line beam position in the surface of the fuel rod is imaged as the parabolic beam in the high definition CCD or CMOS image sensor. From the parabolic beam pattern, the ellipse model is extracted. And the slope of the long and the short axis of the ellipse model is found. The crossing point between the saddle point of the parabolic beam and the long & short axis of the ellipse model is taken as the feature of the deformed fuel rod. The vertical offset between feature points before and after fuel rod deformation is calculated. From the experimental results, $50\;{\mu}m$ inspection resolution is acquired using the proposed method, which is three times enhanced than the conventional criterion ($150\;{\mu}m$) of the guide for the inspection of the nuclear fuel rod.