• Title/Summary/Keyword: Contour Detection

Search Result 227, Processing Time 0.023 seconds

Detection of Tongue Area using Active Contour Model (능동 윤곽선 모델을 이용한 혀 영역의 검출)

  • Han, Young-Hwan
    • Journal of rehabilitation welfare engineering & assistive technology
    • /
    • v.10 no.2
    • /
    • pp.141-146
    • /
    • 2016
  • In this paper, we apply limited area mask operation and active contour model to accurately detect tongue area outline in tongue diagnosis system. To accurately analyze the properties of the tongue, first, the tongue area to be detected. Therefore an effective segmentation method for detecting the edge of tongue is very important. It experimented with tongue image DB consists of 20~30 students 30 people. Experiments on real tongue image show the good performance of this method. Experimental results show that the proposed method extracts object boundaries more accurately than existing methods without mask operation.

Face Contour Detection by Using B-spline Snake for Creating Human Face Caricature

  • Lee, Jang-Hee;Woo, Jae-Kun;Hoon Kang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2003.09a
    • /
    • pp.399-402
    • /
    • 2003
  • This paper deals with the making avatar like a caricature from human face image which is made by web camera. Generally, the Image made by web camera is not low quality but also, there are always various lights and backgrounds. So, It is impossible to recognize a human face's contour by some methods which only find some feature points of a image. Therefore, In this paper, we propose a new method for overcoming defeat of that methods. First, we got the area of human face roughly by color information. And then, we could find the exact human face's contour by using B-spline Snake.

  • PDF

A Study on the Detection and the Correction of Prosodic Errors Produced by Chinese Korean-Learners (중국인 학습자들의 한국어 강세구 실현양상과 오류진단 및 교정방안 연구)

  • Yune, Young-Sook
    • Phonetics and Speech Sciences
    • /
    • v.4 no.2
    • /
    • pp.51-59
    • /
    • 2012
  • The purpose of this study is to examine the pitch pattern of Korean accentual phrases produced by Chinese Korean-learners in the reading of a Korean text. Korean accentual phrase is determined by a specific F0 contour. And the pitch contour of APs differ depending on their length and the nature of initial segment. In order to examine if Chinese speakers are also aware such a phonetic properties, we have examined the AP pitch contours produced by 15 Chinese speakers differing in proficiency, and compared them to pitch contours produced by six Korean native speakers. The results show that Chinese speakers' pitch errors were observed in initial segment-tone interaction and in type of pitch patterns. However, even though Chines speakers produced the same type of pitch patterns, internal tonal modulation differs from native speakers. Finally, on the basis of theses results, we proposed a teaching method that visualizes the F0 contour.

A Fast Detection of Change Regions using Test Statistics (검정 통계량을 이용한 고속 변화 영역 검출)

  • Chung, Yoon-Su;Kim, Jin-Seok;Kim, Jae-Han;Lee, Kil-Heum
    • Journal of KIISE:Software and Applications
    • /
    • v.27 no.3
    • /
    • pp.241-247
    • /
    • 2000
  • In this paper, a fast change detection is proposed for sequence image. The proposed method enhances the quality of the change detection mask and the speed of the change detection by combining block based method and pixel based method. Firstly, change regions are detected for 16 ${\times}$ 16 blocks in image. And 16 ${\times}$ 16 contour block of change detection mask is divided into 4 subblocks. Finally, for divided 8 ${\times}$ 8 blocks, contour blocks are extracted and then, the pixel-based change regions are detected for them. As this makes use of the block based method, this not only enhances the speed of the change detection, but also reduces effects of noise in change detection mask. Experimental results show not only the improvement of the separated change/non-change region, but also the improvement of the speed.

  • PDF

Real-Time Object Tracking Algorithm based on Minimal Contour in Surveillance Networks (서베일런스 네트워크에서 최소 윤곽을 기초로 하는 실시간 객체 추적 알고리즘)

  • Kang, Sung-Kwan;Park, Yang-Jae
    • Journal of Digital Convergence
    • /
    • v.12 no.8
    • /
    • pp.337-343
    • /
    • 2014
  • This paper proposes a minimal contour tracking algorithm that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. This algorithm perform detection for object tracking and when it transmit image data to server from camera, it minimized communication load by reducing quantity of transmission data. This algorithm use minimal tracking area based on the kinematics of the object. The modeling of object's kinematics allows for pruning out part of the tracking area that cannot be mechanically visited by the mobile object within scheduled time. In applications to detect an object in real time,when transmitting a large amount of image data it is possible to reduce the transmission load.

A System for Recognizing Sunglasses and a Mask of an ATM User (현금 인출기 사용자의 선글라스 및 마스크 인식 시스템)

  • Lim, Dong-Ak;Ko, Jae-Pil
    • Journal of Korea Multimedia Society
    • /
    • v.11 no.1
    • /
    • pp.34-43
    • /
    • 2008
  • This paper presents a system for recognizing sunglasses and a mask of an ATM (Automatic Teller Machine) user. The proposed system extracts firstly facial contour, then from this extraction results it estimates the regions of eyes and mouth. Finally, it recognizes sunglasses and a mouth using Histogram Indexing based on those regions. We adopt a face shape model to be able to extract facial contour and to estimate the regions of eyes and mouth when those regions are occluded by sunglasses and a mask. To improve the fitting accuracy of the shame model, we adopt 2-step face detection method and conduct fitting several times by varying the initial position of the model instance. To achieve a good performance of the face detection method based on a background model, we enable the system to automatically update the background model. In experiment, we present some experiments on setting parameters of the system with images taken from in our laboratory, and demonstrate the results of recognizing sunglasses and a mask.

  • PDF

Infant Retinal Images Optic Disk Detection Using Active Contours

  • Charmjuree, Thammanoon;Uyyanonvara, Bunyarit;Makhanov, Stanislav S.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2004.08a
    • /
    • pp.312-316
    • /
    • 2004
  • The paper presents a technique to identify the boundary of the optic disc in infant retinal digital images using an approach based on active contours (snakes). The technique can be used to be develop a automate system in order to help the ophthalmologist's diagnosis the retinopathy of prematurity (ROP) disease which may occurred on preterm infant,. The optic disc detection is one of the fundamental step which could help to create an automate diagnose system for the doctors we use a new kind of active contour (snake) method has been developed by Chenyang et. al. [1], based on a new type of external force field, called gradient vector flow, or GVF. GVF is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The testing results on a set of infant retinal ROP images verify the effectiveness of the proposed methods. We show that GVF has a large capture range and it's able to move snakes into boundary concavities of optic disc and finally the optic disk boundary was determined.

  • PDF

CAD Scheme To Detect Brain Tumour In MR Images using Active Contour Models and Tree Classifiers

  • Helen, R.;Kamaraj, N.
    • Journal of Electrical Engineering and Technology
    • /
    • v.10 no.2
    • /
    • pp.670-675
    • /
    • 2015
  • Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

Door Detection with Door Handle Recognition based on Contour Image and Support Vector Machine (외곽선 영상과 Support Vector Machine 기반의 문고리 인식을 이용한 문 탐지)

  • Lee, Dong-Wook;Park, Joong-Tae;Song, Jae-Bok
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.16 no.12
    • /
    • pp.1226-1232
    • /
    • 2010
  • A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.

Direct Slicing with Optimum Number of Contour Points

  • Gupta Tanay;Chandila Parveen Kumar;Tripathi Vyomkesh;Choudhury Asimava Roy
    • International Journal of CAD/CAM
    • /
    • v.4 no.1
    • /
    • pp.33-45
    • /
    • 2004
  • In this work, a rational procedure has been formulated for the selection of points approximating slice contours cut in LOM (Laminated Object manufacturing) with first order approximation. It is suggested that the number of points representing a slice contour can be 'minimised' or 'optmised' by equating the horizontal chordal deviation (HCD) to the user-defined surface form tolerance. It has been shown that such optimization leads to substantial reduction in slice height calculations and NC codes file size for cutting out the slices. Due to optimization, the number of contour points varies from layer to layer, so that points on successive layer contours have to be matched by four sided ruled surface patches and triangular patches. The technological problems associated with the cutting out of triangular patches have been addressed. A robust algorithm has been developed for the determination of slice height for optimum and arbitrary numbers of contour points with different strategies for error calculations. It has been shown that optimisation may even lead to detection and appropriate representation of elusive surface features. An index of optimisation has been defined and calculations of the same have been tabulated.