Local Triangular Coded Pattern: A Texture Descriptor for Image Classification

ABSTRACT

Local binary descriptors are extensively used for image representation in many of the computer vision applications. A majority of these local binary descriptors exploit the intensity difference of the neighbouring pixels with respect to the centre pixel of the chosen region to formulate the representative value at the respective pixel position. In this paper, a novel descriptor, called Local Triangular Coded Pattern (LTCP), is introduced that utilises the relationship between a set of pixels in the triangular neighbourhood of a region to compute the descriptor. Unlike many of the other local binary descriptors, the proposed descriptor considers multiple pixels as centres within the given region to obtain the binary pattern. The performance of the LTCP descriptor is analysed by performing image classification in benchmarked texture datasets such as KTH-TIPS, Outex, Brodatz and Kylergb and in facial emotion datasets such as CK+, JAFFE, MUFE and Yale Face. The results indicate that LTCP with the Random Forest classifier gives an accuracy of 92.82%, 93.81%, 94.11% and 97.14%, respectively, on Brodatz, Outex, KTH-TIPS and Kylergb datasets for texture classification and 97.52%, 95.52%, 96.13% and 93.88%, respectively, on CK+, JAFFE, MUFE and Yale Face datasets for emotion classification. The experimental findings reflect the LTCP descriptor’s dominance and robustness over others.

Keywords:

• Emotion classification
• Local binary descriptors
• Random Forest
• Texture analysis
• Tri-code pattern

Additional information

Notes on contributors

R. Arya

Arya R received her BCA from Mahatma Gandhi University, Kerala, India, MCA and MPhil in Computer Science from Amrita Vishwa Vidyapeetham University, India. Presently, she is working on her PhD in the area of image processing at Amrita Vishwa Vidyapeetham University, Kochi. Her areas of research interest are image classification, content-based image retrieval, data mining and video analytics.

E. R. Vimina

Vimina E R received her BTech degree in electrical and electronics engineering from Mahatma Gandhi University, Kerala, India, ME degree in computer science and engineering from Bharathiyar University, Tamilnadu, India and PhD degree from Cochin University of Science and Technology, Kerala, India. Presently, she is working as an assistant professor in the Department of Computer Science and IT of Amrita Vishwa Vidyapeetham, Kochi campus, India. Her major fields of interest are content-based image retrieval, biomedical imaging and video analysis. Email: [email protected]