Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Detecting Edges in Images Using Bat Optimization Based on Interval Type-2 Fuzzy Logic


Affiliations
1 Chikkanna Government Arts College, Tiruppur, India
2 Department of Mathematics, Chikkanna Government Arts College, Tiruppur, India
3 Department of Mathematics, Chikkanna Government Arts College, Tiruppur, India
     

   Subscribe/Renew Journal


In this work, Edge detection in Digital images based on Morphological Gradient using Interval Type-2 Fuzzy logic is studied. In order to improve the efficiency of this algorithm, Bat optimization is introduced. Performance of this method is tested with some benchmark images and the results are compared with type-1 fuzzy inference system (T1FIS) and Interval type-2 fuzzy inference system (IT2FIS). Result indicate that image obtained with this new method is better than the existing methods.


Keywords

Digital Images, Edge Detection, Bat Optimization, Interval Type-2 Fuzzy Logic.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 235

PDF Views: 1




  • Detecting Edges in Images Using Bat Optimization Based on Interval Type-2 Fuzzy Logic

Abstract Views: 235  |  PDF Views: 1

Authors

Chitra
Chikkanna Government Arts College, Tiruppur, India
RajaRajeswari
Department of Mathematics, Chikkanna Government Arts College, Tiruppur, India
Radharamani
Department of Mathematics, Chikkanna Government Arts College, Tiruppur, India

Abstract


In this work, Edge detection in Digital images based on Morphological Gradient using Interval Type-2 Fuzzy logic is studied. In order to improve the efficiency of this algorithm, Bat optimization is introduced. Performance of this method is tested with some benchmark images and the results are compared with type-1 fuzzy inference system (T1FIS) and Interval type-2 fuzzy inference system (IT2FIS). Result indicate that image obtained with this new method is better than the existing methods.


Keywords


Digital Images, Edge Detection, Bat Optimization, Interval Type-2 Fuzzy Logic.