Three-Level Broad-Edge Template Matching and Its Application to Real-Time Vision System

Kazuhiko SUMI  Manabu HASHIMOTO  Haruhisa OKUDA  Shin'ichi KURODA 

Publication
IEICE TRANSACTIONS on Information and Systems  Vol.E78-D  No.12  pp.1526-1532
Publication Date: 1995/12/20
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Machine Vision Applications)
Category: 
Keyword: 
three-level image,  Lapracian-Gaussian,  template matching,  cross-correlation,  real-time,  industrial application, 

Full Text: PDF(645.3KB)

Summary: 
This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 3232 image model search from the 128128 pixel area in 2 milli-seconds with a 9 MHz pixel clock image processor. This speed is fast enough for searching and tracking a single object at video frame rate.