• Title/Summary/Keyword: Feature line

Search Result 860, Processing Time 0.028 seconds

Generation of Feature Map for Improving Localization of Mobile Robot based on Stereo Camera (스테레오 카메라 기반 모바일 로봇의 위치 추정 향상을 위한 특징맵 생성)

  • Kim, Eun-Kyeong;Kim, Sung-Shin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.13 no.1
    • /
    • pp.58-63
    • /
    • 2020
  • This paper proposes the method for improving the localization accuracy of the mobile robot based on the stereo camera. To restore the position information from stereo images obtained by the stereo camera, the corresponding point which corresponds to one pixel on the left image should be found on the right image. For this, there is the general method to search for corresponding point by calculating the similarity of pixel with pixels on the epipolar line. However, there are some disadvantages because all pixels on the epipolar line should be calculated and the similarity is calculated by only pixel value like RGB color space. To make up for this weak point, this paper implements the method to search for the corresponding point simply by calculating the gap of x-coordinate when the feature points, which are extracted by feature extraction and matched by feature matching method, are a pair and located on the same y-coordinate on the left/right image. In addition, the proposed method tries to preserve the number of feature points as much as possible by finding the corresponding points through the conventional algorithm in case of unmatched features. Because the number of the feature points has effect on the accuracy of the localization. The position of the mobile robot is compensated based on 3-D coordinates of the features which are restored by the feature points and corresponding points. As experimental results, by the proposed method, the number of the feature points are increased for compensating the position and the position of the mobile robot can be compensated more than only feature extraction.

Improving Matching Performance of SURF Using Color and Relative Position (위치와 색상 정보를 사용한 SURF 정합 성능 향상 기법)

  • Lee, KyungSeung;Kim, Daehoon;Rho, Seungmin;Hwang, Eenjun
    • Journal of Advanced Navigation Technology
    • /
    • v.16 no.2
    • /
    • pp.394-400
    • /
    • 2012
  • SURF is a robust local invariant feature descriptor and has been used in many applications such as object recognition. Even though this algorithm has similar matching accuracy compared to the SIFT, which is another popular feature extraction algorithm, it has advantage in matching time. However, these descriptors do not consider relative location information of extracted interesting points to guarantee rotation invariance. Also, since they use gray image of original color image, they do not use the color information of images, either. In this paper, we propose a method for improving matching performance of SURF descriptor using the color and relative location information of interest points. The location information is built from the angles between the line connecting the centers of interest points and the orientation line constructed for the center of each interest points. For the color information, color histogram is constructed for the region of each interest point. We show the performance of our scheme through experiments.

Two-Dimensional Shape Description of Objects using The Contour Fluctuation Ratio (윤곽선 변동율을 이용한 물체의 2차원 형태 기술)

  • 김민기
    • Journal of Korea Multimedia Society
    • /
    • v.5 no.2
    • /
    • pp.158-166
    • /
    • 2002
  • In this paper, we proposed a contour shape description method which use the CFR(contour fluctuation ratio) feature. The CFR is the ratio of the line length to the curve length of a contour segment. The line length means the distance of two end points on a contour segment, and the curve length means the sum of distance of all adjacent two points on a contour segment. We should acquire rotation and scale invariant contour segments because each CFR is computed from contour segments. By using the interleaved contour segment of which length is proportion to the entire contour length and which is generated from all the points on contour, we could acquire rotation and scale invariant contour segments. The CFR can describes the local or global feature of contour shape according to the unit length of contour segment. Therefore we describe the shape of objects with the feature vector which represents the distribution of CFRs, and calculate the similarity by comparing the feature vector of corresponding unit length segments. We implemented the proposed method and experimented with rotated and scaled 165 fish images of fifteen types. The experimental result shows that the proposed method is not only invariant to rotation and scale but also superior to NCCH and TRP method in the clustering power.

  • PDF

The horizontal line detection method using Haar-like features and linear regression in infrared images

  • Park, Byoung Sun;Kim, Jae Hyup
    • Journal of the Korea Society of Computer and Information
    • /
    • v.20 no.12
    • /
    • pp.29-36
    • /
    • 2015
  • In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.

Simplified Representation of Image Contour

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
    • /
    • v.6 no.4
    • /
    • pp.317-322
    • /
    • 2018
  • We use edge detection technique for the input image to extract the entire edges of the object in the image and then select only the edges that construct the outline of the object. By examining the positional relation between these pixels composing the outline, a simplified version of the outline of the object in the input image is generated by removing unnecessary pixels while maintaining the condition of connection of the outline. For each pixel constituting the outline, its direction is calculated by examining the positional relation with the next pixel. Then, we group the consecutive pixels with same direction into one and then change them to a line segment instead of a point. Among those line segments composing the outline of the object, a line segment whose length is smaller than a predefined minimum length of acceptable line segment is removed by merging it into one of the adjacent line segments. As a result, an outline composed of line segments of over a certain length is obtained through this process.

Implementation of the Controller for intelligent Process System Using Neural Network (신경회로망을 이용한 지능형 가공 시스템 제어기 구현)

  • Son, Chang-U;kim, Gwan-Hyeong;Kim, Il;Tak, Han-Ho;Lee, Sang-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2000.11a
    • /
    • pp.376-379
    • /
    • 2000
  • In this paper, this system makes use of the analog infrered rays sensor and converts the feature of fish analog signal when sensor is operating with CPU(80C196KC). Then, After signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error backpropagation is used as a learning algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long time when random initial weights are used, off-line learning is induced to decrease the progress time. We confirmed this method has better performance than somewhat outdated machines.

  • PDF

On the Formative Feature Characteristics of Cyber Character's Fashion in the Cyber-space Game (가상공간 게임에 나타난 사이버 캐릭터 의상의 조형성)

  • 서정립;진경옥
    • Journal of the Korean Society of Costume
    • /
    • v.54 no.3
    • /
    • pp.99-112
    • /
    • 2004
  • The purpose of this research is to examine the relation between the cyber environment and the contemporary fashion design by studying the formative feature characteristics of cyber character's fashion in the on-line game from the point of the contemporary fashion design. The research method is to understand the general concept of the cyber-space and characters and then is to contemplate characteristics and formative features of game character's fashion of the cyber-space mainly with cyber characters that were closely linked with features of the contemporary fashion design. As a result, the formative feature of game character's fashion of the cyber-space was to be classified into four categories; reactionism, mechanism, futurism, sensualism. First, reactionism takes traditional elements with symbolical and compromising form. Second, mechanism has a tendency of deconstruction due to its vitality and sense of velocity for objects through employing geometrical forms and new materials. Third, futurism deviates from the established framework. It makes use of high-tech materials and has surrealistic and futuristic features. Fourth, sensualism does emphasize sensual parts of the body and intends to convey aesthetic atmosphere through association of ideas. Character's fashion of the cyber on-line game is unnatural and artificial in its forms and wear for the lack of knowledge for costume's structure, and it shows just simplified design that accept extremely partial fragment of features in the contemporary fashion design.

Image Feature Extraction Using Independent Component Analysis of Hybrid Fixed Point Algorithm (조합형 Fixed Point 알고리즘의 독립성분분석을 이용한 영상의 특징추출)

  • Cho, Yong-Hyun;Kang, Hyun-Koo
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.6 no.1
    • /
    • pp.23-29
    • /
    • 2003
  • This paper proposes an efficient feature extraction of the images by using independent component analysis(ICA) based on neural networks of the hybrid learning algorithm. The proposed learning algorithm is the fixed point(FP) algorithm based on Newton method and moment. The Newton method, which uses to the tangent line for estimating the root of function, is applied for fast updating the inverse mixing matrix. The moment is also applied for getting the better speed-up by restraining an oscillation due to compute the tangent line. The proposed algorithm has been applied to the 10,000 image patches of $12{\times}12$-pixel that are extracted from 13 natural images. The 144 features of $12{\times}12$-pixel and the 160 features of $16{\times}16$-pixel have been extracted from all patches, respectively. The simulation results show that the extracted features have a localized characteristics being included in the images in space, as well as in frequency and orientation. And the proposed algorithm has better performances of the learning speed than those using the conventional FP algorithm based on Newton method.

  • PDF

A Real-time Vision Inspection System at a Laver Production Line (해태 생산라인에서의 실시간 시각검사 시스템)

  • Kim, Gi-Weon;Kim, Bong-Gi
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2007.06a
    • /
    • pp.601-604
    • /
    • 2007
  • In this paper dose a laver surface check using a real time image process. This system does false retrieval of a laver at a laver production line. At first, a laver image was read in real time using a CCD camera. In this paper, we use an area scan CCD camera. Image is converted into a binary code image using a high-speed imaging process board afterwards. A laver feature is extracted by a binary code image. Surface false retrieval is finally executed using a laver feature. In this paper, we use an area feature of a laver image.

  • PDF

Registration of Aerial Image with Lines using RANSAC Algorithm

  • Ahn, Y.;Shin, S.;Schenk, T.;Cho, W.
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.25 no.6_1
    • /
    • pp.529-536
    • /
    • 2007
  • Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.