MULTI-SCALE EDGE DETECTOR USING GAUSSIAN FILTERING.

Xinhua Zhuang; Thomas S. Huang; Homer H. Chen

MULTI-SCALE EDGE DETECTOR USING GAUSSIAN FILTERING.

Xinhua Zhuang, Thomas S. Huang, Homer H. Chen

Coordinated Science Lab

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The authors give a possible solution to a problem of how to combine effectively the different scales of analysis at the early visual information processing level. The main result is a limit theorem which confirms that in 1-D the convolution difference uniformly and asymptotically approximates the box train function as the size of the Gaussian filter approaches zero. The box train function represents the edge point information in the 1-D image. The modified limit theorem for detecting edge directions is presented.

Original language	English (US)
Title of host publication	Unknown Host Publication Title
Publisher	IEEE
Pages	558-563
Number of pages	6
ISBN (Print)	0818607211
State	Published - 1986

ASJC Scopus subject areas

General Engineering

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title = "MULTI-SCALE EDGE DETECTOR USING GAUSSIAN FILTERING.",

abstract = "The authors give a possible solution to a problem of how to combine effectively the different scales of analysis at the early visual information processing level. The main result is a limit theorem which confirms that in 1-D the convolution difference uniformly and asymptotically approximates the box train function as the size of the Gaussian filter approaches zero. The box train function represents the edge point information in the 1-D image. The modified limit theorem for detecting edge directions is presented.",

author = "Xinhua Zhuang and Huang, {Thomas S.} and Chen, {Homer H.}",

year = "1986",

language = "English (US)",

isbn = "0818607211",

publisher = "IEEE",

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T1 - MULTI-SCALE EDGE DETECTOR USING GAUSSIAN FILTERING.

AU - Zhuang, Xinhua

AU - Huang, Thomas S.

AU - Chen, Homer H.

PY - 1986

Y1 - 1986

N2 - The authors give a possible solution to a problem of how to combine effectively the different scales of analysis at the early visual information processing level. The main result is a limit theorem which confirms that in 1-D the convolution difference uniformly and asymptotically approximates the box train function as the size of the Gaussian filter approaches zero. The box train function represents the edge point information in the 1-D image. The modified limit theorem for detecting edge directions is presented.

AB - The authors give a possible solution to a problem of how to combine effectively the different scales of analysis at the early visual information processing level. The main result is a limit theorem which confirms that in 1-D the convolution difference uniformly and asymptotically approximates the box train function as the size of the Gaussian filter approaches zero. The box train function represents the edge point information in the 1-D image. The modified limit theorem for detecting edge directions is presented.

UR - http://www.scopus.com/inward/record.url?scp=0022565640&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0022565640&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0022565640

SN - 0818607211

SP - 558

EP - 563

BT - Unknown Host Publication Title

PB - IEEE

ER -

MULTI-SCALE EDGE DETECTOR USING GAUSSIAN FILTERING.

Abstract

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