서지주요정보
허프 변환을 이용한 원과 타원의 검출 및 이를 응용한 정면 얼굴의 검출 = Hough transform-based circle and ellipse detection methods and their application to frontal face detection
서명 / 저자 허프 변환을 이용한 원과 타원의 검출 및 이를 응용한 정면 얼굴의 검출 = Hough transform-based circle and ellipse detection methods and their application to frontal face detection / 김흥수.
저자명 김흥수 ; Kim, Heung-Soo
발행사항 [대전 : 한국과학기술원, 2003].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8014398

소장위치/청구기호

학술문화관(문화관) 보존서고

DEE 03006

휴대폰 전송

도서상태

이용가능

대출가능

반납예정일

초록정보

This thesis studies the detection of elliptical shapes, including circles, ellipses and frontal faces, in gray-scale images. Object detection is one of the fundamental problems in computer vision. It includes the detection of elliptical arcs and human faces. Many circular objects are frequently found in the real world, such as in automatic inspection and assembly. The oblique projection of a circle onto an image plane is an ellipse. Detection of faces is indispensable for face recognition systems and useful for man-machine interfaces. This is particularly so for the frontal face, i.e., the front view of a face, which is oval or elliptical. Hough transform (HT) is one of the most popular methods used to detect analytic curves such as lines, circles and ellipses. But, although it is robust to noises, occlusions, shape distortions, etc., it suffers from large memory requirements and high computational loads. To overcome these limitations, many variants of HT have been developed. In this direction, the original contributions of this thesis are based mainly on a new Hough transform called ERHT, applied to ellipse detection and frontal face detection, and a new variant of standard Hough transform, applied to circle detection. The proposed ERHT-based ellipse detector can detect ellipses efficiently with small memory requirements. The proposed circle detector is a two-step algorithm based on the concept of intersecting chords. It can efficiently detect simple circles in an image with very complex background. Both the circle detector and the ellipse detector work on the edge image extracted from the input image. Two methods to detect frontal faces are proposed. The first one is a combination of a GHT-based ellipse detector and a neural network-based face detector. The second one is a combination of an ERHT-based ellipse detector and a neural network-based face detector. Both GHT-based and ERHT-based ellipse detectors are applied to locate the face candidates quickly. The neural network-based face/non-face classifier then verifies each face candidate. The applicability and efficiency of the two proposed methods are experimentally verified using representative face databases.

서지기타정보

서지기타정보
청구기호 {DEE 03006
형태사항 viii, 120 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Heung-Soo Kim
지도교수의 한글표기 : 김종환
지도교수의 영문표기 : Jong-Hwan Kim
수록잡지명 : "A two-step circle detection algorithm from the intersecting chords". Pattern recognition letters, v.22, pp. 787-798 (2001)
학위논문 학위논문(박사) - 한국과학기술원 : 전기및전자공학전공,
서지주기 참고문헌 : p. 109-115
주제 원 검출
타원 검출
정면 얼굴 검출
허프 변환
신경 회로망
circle detection
ellipse detection
frontal face detection
Hough transform
neural network
QR CODE qr code