Paper
1 April 1992 Morphological operations applied on polygon representation of binary images
Olli P. Yli-Harja, Ari M. Vepsalainen
Author Affiliations +
Proceedings Volume 1658, Nonlinear Image Processing III; (1992) https://doi.org/10.1117/12.58371
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States
Abstract
Morphological operations applied to polygon representation of binary images are investigated, with special attention to the implementations of erosion and dilation. Binary images can be compressed by presenting only the outlines of the objects with 4- or 8-neighborhood chain code. The chain code representation of a binary image can be efficiently eroded (or dilated) with 8- or 4-neighborhood kernels, respectively. This method indirectly uses the following idea: applying morphological operations directly to the compressed (chain coded) images involves less data than applying them to the original binary image. The chain-coded binary image can be further compressed by identifying linear segments on the outline of the objects. If the polygon representation of an object requires less space than the chain code representation, then its morphological filtering should also be faster. The shape of the kernel is presented as a polygon. In morphological operations, the polygon node is either replaced by a new node defined by the intersection of the newly formed vertixes or replaced by some transformed nodes of the kernel. After erosion, the newly formed polygon may cross itself. These situations must be checked and the polygon must be broken accordingly to several smaller polygons. Several efficient clipping algorithms exist. However, clipping of polygons is commonly the most time-consuming part of the presented method.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olli P. Yli-Harja and Ari M. Vepsalainen "Morphological operations applied on polygon representation of binary images", Proc. SPIE 1658, Nonlinear Image Processing III, (1 April 1992); https://doi.org/10.1117/12.58371
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KEYWORDS
Binary data

Image segmentation

Image compression

Nonlinear image processing

Transform theory

Image filtering

Mathematical morphology

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