SCALE-INVARIANT AND ORIENTATION-INVARIANT GENERALIZED HOUGH TRANSFORM - A NEW APPROACH

被引:32
作者
JENG, SC
TSAI, WH
机构
[1] NATL CHIAO TUNG UNIV,DEPT COMP & INFORMAT SCI,HSINCHU 30050,TAIWAN
[2] NATL CHIAO TUNG UNIV,INST COMP SCI & INFORMAT ENGN,HSINCHU 30050,TAIWAN
[3] IND TECHNOL RES INST,CTR ADV TECHNOL,COMP & COMMUN RES LABS,HSINCHU 31015,TAIWAN
关键词
GENERALIZED HOUGH TRANSFORM; HOUGH COUNTING SPACE; CELL VALUE INCREMENTATION; POINT SPREAD FUNCTION; SCALE AND ROTATION INVARIANT; SHAPES DETECTION AND LOCATION;
D O I
10.1016/0031-3203(91)90120-T
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The conventional generalized Hough transform (GHT) is useful for detecting or locating translated 2-dimensional (2D) object shapes. However, a weakness of the conventional GHT is that a brute force approach is usually required to handle shape scaling and rotation, resulting in the use of a 4D Hough counting space (HCS). A new version of the GHT, called scale- and orientation-invariant GHT (SOIGHT), is proposed to remove this weakness. The improvement is based on the use of half lines and circles to replace the displacement vectors used in the conventional GHT for cell value incrementation. The required dimensionality of the HCS for the SOIGHT is reduced to 2D so that the storage and computation requirements for cell value incrementation and maximum detection in the HCS can be reduced effectively. Some experimental results are included to demonstrate the applicability of the proposed SOIGHT.
引用
收藏
页码:1037 / 1051
页数:15
相关论文
共 10 条
[1]   GENERALIZING THE HOUGH TRANSFORM TO DETECT ARBITRARY SHAPES [J].
BALLARD, DH .
PATTERN RECOGNITION, 1981, 13 (02) :111-122
[2]  
Ballard DH, 1982, COMPUTER VISION
[4]   STRUCTURAL SHAPE-RECOGNITION IN A MULTIRESOLUTION ENVIRONMENT [J].
CANTONI, V ;
CARRIOLI, L .
SIGNAL PROCESSING, 1987, 12 (03) :267-276
[6]   USE OF HOUGH TRANSFORMATION TO DETECT LINES AND CURVES IN PICTURES [J].
DUDA, RO ;
HART, PE .
COMMUNICATIONS OF THE ACM, 1972, 15 (01) :11-&
[7]  
Hough P.V.C., 1962, US Patent, Patent No. 3069654
[8]  
KRICHNAPURAM R, 1987, COMPUTER VISION GRAP, V38, P299
[9]  
MERLINPM, 1975, IEEE T COMPUT, V24, P96
[10]  
Rosenfeld A., 1982, DIGITAL PICTURE PROC, V2nd