Image classification using hybrid neural networks

Use of semantic content is one of the major issues which needs to be addressed for improving image retrieval effectiveness. We present a new approach to classify images based on the combination of image processing techniques and hybrid neural networks. Multiple keywords are assigned to an image to represent its main contents, i.e. semantic content. Images are divided into a number of regions and colour and texture features are extracted. The first classifier, a self-organising map (SOM) clusters similar images based on the extracted features. Then, regions of the representative images of these clusters were labeled and used to train the second classifier, composed of several support vector machines (SVMs). Initial experiments on the accuracy of keyword assignment for a small vocabulary are reported. Categories and Subject Descriptors H3.1 [Content Analysis and Indexing]: Indexing Method; I4.6 [Segmentation]: Region growing, partitioning General Terms Measurement, Experimentation Keywo...

• Type: Conference
• Year: 2003
• Where: SIGIR
• Authors: Chih-Fong Tsai, Kenneth McGarry, John Tait
• Keywords: Image, Image Retrieval, Semantic Content, SIGIR 2003