Title :
Image texture classification using Artificial Neural Network (ANN)
Author :
Ahmed, Shohel Ali ; Dey, Snigdha ; Sarma, Kandarpa Kumar
Author_Institution :
Dept. of Electron. & Commun. Technol., Gauhati Univ., Guwahati, India
Abstract :
Texture classification is an important and challenging factor in image processing system which refers to the process of partitioning a digital image into multiple constituent segments. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Artificial Neural Network (ANN) Based texture classification or Segmentation is an advanced technique providing rich information of an image of interest. As a part the work, an ANN is implemented to segment the image. For that a particular type of ANN is configured and trained so that it becomes capable of segmenting an image. The current work deals with a task where an object of interest is to be segmented out of a background for processes which can be carried out as part of extended applications.
Keywords :
image classification; image representation; image segmentation; image texture; neural nets; artificial neural network; digital image partitioning; image processing system; image representation; image texture classification; texture segmentation; Artificial neural networks; Classification algorithms; Feature extraction; Image segmentation; Neurons; Pixel; Training; ANN; Gray level; MLP; MSE; Pixel;
Conference_Titel :
Emerging Trends and Applications in Computer Science (NCETACS), 2011 2nd National Conference on
Conference_Location :
Shillong
Print_ISBN :
978-1-4244-9578-8
DOI :
10.1109/NCETACS.2011.5751383