Sub-pixel localization algorithm of micro-vision based on Hough transform

Dai Dong; Ming Lei Sun; Jing Xin Shi; Rong Liu; Guang Hua Zong

Sub-pixel localization algorithm of micro-vision based on Hough transform

Dai Dong^*
, Ming Lei Sun
, Jing Xin Shi
, Rong Liu
, Guang Hua Zong

^*此作品的通讯作者

机械工程及自动化学院

Beijing Aerospace Control Device Institute
Beihang University

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

According to geometric characteristics of micro-image, sub-pixel localization algorithm of crisscross image based on Hough transform (SLACHT) and sub-pixel localization algorithm of round image based on Hough transform (SLACHT) are presented. Sub-pixel localization of linear and round image of micro-image is studied in detail. In contrast with classic Hough transform (HT) algorithm detecting straight line and classic random Hough transform (RHT) algorithm detecting circle, CSLHT and RSLHT show more advantages. Reliability of the algorithms is proved by comparing with algorithm written by Matlab software. Many experiments show that localization accuracy of the algorithms is less than 0.01 pixel, and that they are accurate, running fast and strong robust.

源语言	英语
页（从-至）	28-37+66
期刊	Guangdian Gongcheng/Opto-Electronic Engineering
卷	33
期	10
出版状态	已出版 - 10月 2006

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引用此

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title = "Sub-pixel localization algorithm of micro-vision based on Hough transform",

abstract = "According to geometric characteristics of micro-image, sub-pixel localization algorithm of crisscross image based on Hough transform (SLACHT) and sub-pixel localization algorithm of round image based on Hough transform (SLACHT) are presented. Sub-pixel localization of linear and round image of micro-image is studied in detail. In contrast with classic Hough transform (HT) algorithm detecting straight line and classic random Hough transform (RHT) algorithm detecting circle, CSLHT and RSLHT show more advantages. Reliability of the algorithms is proved by comparing with algorithm written by Matlab software. Many experiments show that localization accuracy of the algorithms is less than 0.01 pixel, and that they are accurate, running fast and strong robust.",

keywords = "Edge detection, Hough transform, Micro-image, Sub-pixel localization",

author = "Dai Dong and Sun, \{Ming Lei\} and Shi, \{Jing Xin\} and Rong Liu and Zong, \{Guang Hua\}",

year = "2006",

month = oct,

language = "英语",

volume = "33",

pages = "28--37+66",

journal = "Guangdian Gongcheng/Opto-Electronic Engineering",

issn = "1003-501X",

publisher = "Chinese Academy of Sciences",

number = "10",

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TY - JOUR

T1 - Sub-pixel localization algorithm of micro-vision based on Hough transform

AU - Dong, Dai

AU - Sun, Ming Lei

AU - Shi, Jing Xin

AU - Liu, Rong

AU - Zong, Guang Hua

PY - 2006/10

Y1 - 2006/10

N2 - According to geometric characteristics of micro-image, sub-pixel localization algorithm of crisscross image based on Hough transform (SLACHT) and sub-pixel localization algorithm of round image based on Hough transform (SLACHT) are presented. Sub-pixel localization of linear and round image of micro-image is studied in detail. In contrast with classic Hough transform (HT) algorithm detecting straight line and classic random Hough transform (RHT) algorithm detecting circle, CSLHT and RSLHT show more advantages. Reliability of the algorithms is proved by comparing with algorithm written by Matlab software. Many experiments show that localization accuracy of the algorithms is less than 0.01 pixel, and that they are accurate, running fast and strong robust.

AB - According to geometric characteristics of micro-image, sub-pixel localization algorithm of crisscross image based on Hough transform (SLACHT) and sub-pixel localization algorithm of round image based on Hough transform (SLACHT) are presented. Sub-pixel localization of linear and round image of micro-image is studied in detail. In contrast with classic Hough transform (HT) algorithm detecting straight line and classic random Hough transform (RHT) algorithm detecting circle, CSLHT and RSLHT show more advantages. Reliability of the algorithms is proved by comparing with algorithm written by Matlab software. Many experiments show that localization accuracy of the algorithms is less than 0.01 pixel, and that they are accurate, running fast and strong robust.

KW - Edge detection

KW - Hough transform

KW - Micro-image

KW - Sub-pixel localization

UR - https://www.scopus.com/pages/publications/33845914575

M3 - 文章

AN - SCOPUS:33845914575

SN - 1003-501X

VL - 33

SP - 28-37+66

JO - Guangdian Gongcheng/Opto-Electronic Engineering

JF - Guangdian Gongcheng/Opto-Electronic Engineering

IS - 10

ER -

Sub-pixel localization algorithm of micro-vision based on Hough transform

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