A cortex-like model for animal recognition based on texture using feature-selective hashing

Author

Seifzadeh, Sepideh ; Faez, Karim

Author_Institution

Dept. of Electr., Comput. & Biomed. Eng., Islamic Univ., Qazvin, Iran

fYear

2014

fDate

4-6 Feb. 2014

Firstpage

1

Lastpage

4

Abstract

Building a model that can mimic the brain´s cortex has always been a major goal, because the human brain recognizes objects in terms of speed, reliability and flexibility that are always unique pattern for machine vision systems. In this paper, we are inspired by neuroscience and computer science that have designed a framework that can be fast and accurate emulation of the inferior temporal cortex with feature selective hashing to recognize animals. We worked on KTH database containing 1239 images in 13 classes that took photos from animals in wild.

Keywords

computer vision; image recognition; image texture; KTH database; animal recognition; brain cortex; computer science; cortex-like model; feature-selective hashing; image texture; inferior temporal cortex; machine vision systems; neuroscience; Accuracy; Algorithm design and analysis; Animals; Brain modeling; Databases; Feature extraction; Shape; Cortex-like model; animal recognition; feature-selective Hashing; textural fearure extraction;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (ICIS), 2014 Iranian Conference on

Conference_Location

Bam

Print_ISBN

978-1-4799-3350-1

Type

conf

DOI

10.1109/IranianCIS.2014.6802584

Filename

6802584