Neural Networks in Image Processing: A Review of Current Applications

Sheng, Hung Chung and Logeswaran, Rajasvaran (2006) Neural Networks in Image Processing: A Review of Current Applications. INTI Journal, 2 (1). pp. 582-592. ISSN 1675-0284

Preview

Text 2006_7.pdf Download (1MB) | Preview

Abstract

This paper describes current applications of neural networks in image processing. Artificial neural networks (ANNs) are methods of computation and information processing modelled by the brain. Many recent attempts to improve the flexibility and effectiveness of ANNs have focused on the implementation level. In this article, we look into ANNs used in the different stages of image processing, specifically in the preprocessing, data reduction, segmentation, object recognition and image understanding phases. The focus is on current and future ANNs, including feed-forward networks, Kohonen feature maps, Hopfleld networks, goal-seeking neuron (GSN) and cellular neural network (CNN). New types of ANNs are fast increasing. Through this survey of introducing the findings, implementations and recent advances of ANNs in Image processing, it is hoped that this paper will serve as a summary, or base to accelerate further development and use of ANN5 in the field of image processing, and improving the accuracy and speed of image processing tasks in the future.

Actions (login required)

View Item