Morphological filtering of multi-level image using entropy

Author

Choi, Jong-Ho ; Ko, Duck-Young

Author_Institution

Dept. of Electron. Eng., Kang-Nam Univ., Kyunggi, South Korea

Volume

2

fYear

1999

fDate

36495

Firstpage

1279

Abstract

This paper presents new properties of the discrete morphological skeleton representation of binary images, for lossless binary image compression, that is based on these properties. We proposed a morphological recognition algorithm using threshold linear superposition theory to analyze the distribution of randomly spaced and oriented blob shaped particles. We recognized the size and position of randomly shaped particles by using the hit/miss transform. We also illustrate the improvement mathematical morphology makes on the entropy thresholding of small targets

Keywords

data compression; filtering theory; image coding; image recognition; image representation; image thinning; mathematical morphology; maximum entropy methods; random processes; transform coding; discrete morphological skeleton representation; entropy thresholding; hit/miss transform; lossless binary image compression; mathematical morphology; maximum entropy; morphological filtering; morphological recognition algorithm; multi-level image; randomly oriented blob shaped particles distribution; randomly spaced shaped particles distribution; small targets; threshold linear superposition theory; Entropy; Filtering; Image analysis; Image processing; Image recognition; Morphological operations; Morphology; Shape; Signal processing algorithms; Skeleton;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 99. Proceedings of the IEEE Region 10 Conference

Conference_Location

Cheju Island

Print_ISBN

0-7803-5739-6

Type

conf

DOI

10.1109/TENCON.1999.818662

Filename

818662