Automatic leukocytes classification by distance transform, moment invariant, morphological features, gray level co-occurrence matrices and SVM

DOI

10.2991/icismme-15.2015.231How to use a DOI?

Keywords

Leukocytes classification; Euclidean distance transform; Moment invariant; Morphological features; Texture features; Support vector machine.

Abstract

Leukocyte is an important part of the immune system. According to the problem that manual operation is not efficient, a novel automatic classification of leukocytes is proposed in this paper. First, moment invariant based on Euclidean distance transform is extracted from nucleus area and morphological features are extracted from segmented cells. Then, monocytes, lymphocytes and basophils are distinguishing from the other samples using features extracted from the first step. Next, the gray level co-occurrence matrices (GLCM) are used as texture measure to classify the remaining classes via a Support Vector Machine (SVM). Experimental results show that the proposed approach provided good classification accuracy, and sufficiently fast to be used in hematological laboratories.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Gai Pang
AU  - Yangkai Zhuang
AU  - Ping Zhou
PY  - 2015/07
DA  - 2015/07
TI  - Automatic leukocytes classification by distance transform, moment invariant, morphological features, gray level co-occurrence matrices and SVM
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 1089
EP  - 1094
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.231
DO  - 10.2991/icismme-15.2015.231
ID  - Pang2015/07
ER  -