Rotation invariant texture recognition by using Neighbor Discriminant Feature Transform and reinforcement learning

Author

Jundang, Nattapong ; Ongkittikul, Surachai

Author_Institution

Fac. of Eng., Mahanakorn Univ. of Technol., Bangkok, Thailand

fYear

2014

fDate

19-21 March 2014

Firstpage

1

Lastpage

4

Abstract

This paper presents the method of image texture recognition by Volume Trace Transform-VTT, based on several Trace function. All of 10 trace functions will be selected by the reinforcement learning process and constructed to produce noticeable features. The next process is to sum the results of each function together by “NDFT - Neighbor Discriminant Feature Transform”, this process will all the results from the different positions of image results and construct 2-D histogram. The histogram is evaluated by chi-square statistic test and the process works on the basis of brodatz texture and vision texture database.

Keywords

image recognition; image texture; learning (artificial intelligence); statistical testing; transforms; 2D histogram; NDFT; VTT; chisquare statistic test; neighbor discriminant feature transform; reinforcement learning process; rotation invariant image texture recognition; vision texture database; volume trace transform; Databases; Measurement; Transforms; reinforcement learning; trace transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering Congress (iEECON), 2014 International

Conference_Location

Chonburi

Type

conf

DOI

10.1109/iEECON.2014.6925837

Filename

6925837