Mathematical Morphology and Its Application in Machine Vision

David G. Daut; Dongming Zhao

doi:10.1117/12.970030

1 November 1989 Mathematical Morphology and Its Application in Machine Vision

David G. Daut, Dongming Zhao

Proceedings Volume 1199, Visual Communications and Image Processing IV; (1989) https://doi.org/10.1117/12.970030
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

Mathematical morphology provides an efficient tool for image analysis. We study the problem of flaw detection in materials which are represented by very poor contrast digital images. An algorithm for flaw detection in the case of glass matte surfaces has been developed. The object skeletons within the binary images are obtained and directional connectivity information in the skeletons is used to discriminate noise patterns from flaws according to a specified criteria. After the discrimination process, the remaining skeletons correspond to flaws and can be employed to recover the shape of flaws. An alarm flag may be turned on if the sizes of the detected flaws are found to exceed industrial standards. In the case of a grayscale image, the image is converted to a binary version by using an adaptive threshold algorithm, then the algorithm for binary images is applied. Experimental results have been obtained for both binary and grayscale digital image data.

Citation Download Citation

David G. Daut and Dongming Zhao "Mathematical Morphology and Its Application in Machine Vision", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970030

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available