Efficient shape transformations on a massively parallel processor

Andreas I. Svolos; Charalampos Konstantopoulos; Christos Kaklamanis

doi:10.1117/12.341095

5 March 1999 Efficient shape transformations on a massively parallel processor

Andreas I. Svolos, Charalampos Konstantopoulos, Christos Kaklamanis

Proceedings Volume 3646, Nonlinear Image Processing X; (1999) https://doi.org/10.1117/12.341095
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

One of the most important features in image analysis is shape. Problems regarding shape are widely encountered in image processing applications, such as machine vision recognition, visually guided robots, analysis of biomedical images, etc. Mathematical morphology is the branch of image processing that deals with shape analysis. The definition of all morphological transformations is based on two primitive operations, namely dilation and erosion. Since many applications require the solution of morphological problems in real time, the efficient implementation of these operations, in terms of computational time, is crucial. In this paper, two algorithms for the dilation and erosion on an advanced associative processor are presented and evaluated. It is shown that these algorithms can take full advantage of the capabilities of the advanced architecture. Specifically, the ability to access all memory words in parallel leads to synchronous rapid execution of any image translation dictated by the structuring elements employed for morphological processing. The interconnection network allows the efficient implementation of image translations at any number of pixels. Also, the ability to perform logic operations parallel on the bits in each processing element leads to optimal computational complexity. Finally, it is shown that there is a trade-off between circuit complexity and communication delay.

Citation Download Citation

Andreas I. Svolos, Charalampos Konstantopoulos, and Christos Kaklamanis "Efficient shape transformations on a massively parallel processor", Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); https://doi.org/10.1117/12.341095

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