Image Processing based Linear Discriminant and Quadratic Discriminant Classifier for Feature Extraction Models

被引：0
|
作者：
Pandarge, Supriya S. [1 ]
Ratnaparkhe, Varsha R. [1 ]
机构：
[1] Govt Coll Engn, Elect & Telecommun Engn Dept, Aurangabad, Maharashtra, India
来源：
PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS) | 2019年
关键词：
image classification; Red Blood Cells (RBC); feature extraction; classifier; combiner;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An automatic method for classification of RBCs is discussed in this paper to overcome the limitations of manual analysis. This is helpful for fast, precise and efficient analysis of blood cells in order to diagnose diseases. Wavelet transform and thresholding techniques are used for feature extraction. Two classifiers and three combining rules are implemented with PR Toolbox. LDC and QDC classifiers are used separately and then combined. Highest accuracy of 85% is obtained by LDC. Meanc Productc combiner rule gives highest accuracy of 90%. Source coding is performed in MATLAB R2016a.
引用
收藏
页码：1502 / 1505
页数：4
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