A novel image segmentation utilizing FUZZY-based LBP and active contour model

ABSTRACT

This work presents an object recognition algorithm that combines local binary pattern (LBP) based on fuzzy logic approach and active contour model for segmenting different images to detect textured objects. Initially, images containing objects are segmented using the fuzzy logic-optimized LBP method. Then, we eliminate the image noise. Finally, utilizing a Chan-Vese active contour method, the target object of the image is highlighted. The segmentation has been compared with the classical LBP technique and the results indicated higher accuracy and quality for highlighting the object from the background. The classification of highlighted objects is performed with a convolution neural network (CNN). To authenticate the proposed approach, 140 images with the classification of 10 different objects were used. The simulation depicted that the proposed method has better results than other methods both in terms of segmentation error and performance. Significantly, CNN classification also showed a classification accuracy of 92.8%.

KEYWORDS:

• Segmentation
• active contour model
• local binary pattern
• fuzzy logic
• feature extraction
• CNN
• classification
• segmentation error
• accuracy

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Mojtaba Sajadi

Mojtaba Sajadi was born in Arak, Iran in 1970. He received the BSc degree from Tehran Telecommunication Faculty with a focus on Telecommunication in 1999 and MSc degree from Azad University, South Branch of Tehran, 2003. Currently, he is PhD student at Arak Azad University. Email: [email protected]

Mohammad Bagher Tavakoli

Mohammad Bagher Tavakoli was born in Arak, Iran, in 1978. He received PhD degree from Science and Research Branch, Islamic Azad University in 2013. He received MS and BS degrees from the Department of Electronic, Arak Branch, Islamic Azad University in 2006 and 2003, respectively. He became an associate professor at the Islamic Azad University of Arak in 2013. He is a Deputy of the Faculty of Engineering in the Islamic Azad University of Arak. Corresponding author. Email: [email protected]

Farbod Setoudeh

Farbod Setoudeh is currently an assistant professor of Electrical engineering with the Department of Electrical and Computer Engineering, Arak University of Technology, Arak, Iran. He received the BSc degree in Electrical Engineering, and MSc degree in Electronic Engineering from Islamic Azad University, Arak, Iran, in 2006, and 2008, respectively and received the Ph.D. degree in Electrical Engineering (Electronic) from Science and Research Branch, Islamic Azad University, Tehran, Iran in 2014. His research interests are linear and non-linear control system and systems identification, Neural Networks, Modelling, stability, circuit design, Earthquake Prediction, and design of microstrip filters. E-mail: [email protected]

Amir Hossein Salemi

Amir Hossein Salemi was born in Arak, Iran in 1966. He received the BSc degree in Electrical Engineering from Sharif University of Technology in 1990 and MSc degree in Electrical Engineering in 1995 from Amirkabir University of Technology. He received the Ph.D. in Electrical Engineering from Amirkabir University of Technology in 2005. Currently, he is Assistant Professor at the Islamic Azad University of Arak. E-mail: [email protected]