The Study of Classifier Detection Time Based on OpenCV

Author

Taotao Dai ; Yuchao Dou ; Hua Tian ; Ziqiang Huang

Author_Institution

Res. Inst. Electron. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

Volume

2

fYear

2012

fDate

28-29 Oct. 2012

Firstpage

466

Lastpage

469

Abstract

OpenCV can be used to detect picture modes with good effect. Here this paper will focus on detecting the palm. and the key step for palm detecting is to train a classifier. Therefore, the main content of the article is to train a classifier and test the classifier. before training a classifier, it is necessary to get a lot of samples and them handle them. after training, there will be some experiments to study the factor which will affect on the detection time. Then, go to the source code of OpenCV, and find the relationship finally. at last, a good classifier is proposed.

Keywords

image classification; palmprint recognition; software libraries; OpenCV; classifier detection time; classifier training; palm detection; picture mode detection; source code; Classification algorithms; Computer vision; Eigenvalues and eigenfunctions; Feature extraction; Software; Testing; Training; classifier; detection time; false positive rate; sample; scaleFactor; training size;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-2646-9

Type

conf

DOI

10.1109/ISCID.2012.286

Filename

6406039