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Influence of normalization and color features on super-pixel classification: application to cytological image segmentation.

Abstract：

:Super-pixel feature extraction is a key problem to get an acceptable performance in color super-pixel classification. Given a color feature extraction problem, it is necessary to know which is the best approach to solve this problem. In the current work, we're interested in the challenge of nucleus and cytoplasm automatic recognition in the cytological image. We propose an automatic process for white blood cells (WBC) segmentation using super-pixel classification. The process is divided into five steps. In first step, the color normalization is calculated. The super-pixels generation by Simple Linear Iterative Clustering algorithm is performed in the second step. In third step, the color property is used to achieve illumination invariance. In fourth step, color features are calculated on each super-pixel. Finally, supervised learning is realized to classify each super-pixel into nucleus and cytoplasm region. The present work rallied an exhaustive statistical evaluation of a very wide variety of the color super-pixel classification, with height normalization methods, four-color spaces and four feature extraction techniques. Normalization and color spaces slightly increase the average accuracy of super-pixel classification. Our experiments based to statistical comparison allow to conclude that comprehensive gray world normalized normalization is better than without normalization for super-pixel classification achieving the first positions in the Friedman ranking. RGB space is the best color spaces to be used in super-pixel feature extraction for nucleus and cytoplasm segmentation. For feature extraction, the learning methods work better on the first order statistics features for the automatic WBC segmentation.

journal_name

Australas Phys Eng Sci Med

journal_title

Australasian physical & engineering sciences in medicine

authors

Bechar MEA,Settouti N,Daho MEH,Adel M,Chikh MA

doi

10.1007/s13246-019-00735-8

subject

Has Abstract

pub_date

2019-06-01 00:00:00

pages

427-441

issue

eissn

0158-9938

issn

1879-5447

pii

10.1007/s13246-019-00735-8

journal_volume

pub_type

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Influence of normalization and color features on super-pixel classification: application to cytological image segmentation.