Although widely studied for many years, colour image quantisation remains a challenging problem. We propose to use an evolving self-organising map model for the on-line image quantisation tasks. Encouraging results are obtained in experiments and we look forward to implementing the algorithm in real world applications with further improvement.

Self-Organising Maps are a form of neural network allowing unsupervised learning. In this work, we use a 2-dimensional network. Given a set of data, the neural network learns the distribution of data points, and provides a mapping from the set of data points to the neural network. The mapping has the property that similar data points map to nearby neurons in the network. Figure 2. Self-Organisi...

Sinus diagnosis has proven to be a difficult task due to the complexity of the image obtained using the computed Tomography (CT). This makes image processing and analysis difficult and time consuming. The aim of this paper is to investigate and implement a technique for the extraction of healthy maxillary and ethmoid sinuses. The proposed algorithm involves the use of neural network (self-organ...

A method is presented to extract musical features from melodic material. Various viewpoints are defined to focus on complementary aspects of the material. To model the melodic context, two measures of entropy are employed: A set of trained probabilistic models capture local structures via the information-theoretic notion of unpredictability, and an alternative entropymeasure based on adaptive c...

Case-Based Reasoning (CBR) is a methodology that reuses the solutions of previous similar problems to solve new problems. Adaptation is the most difficult stage in the CBR cycle, especially, when the solution space is multi-dimensional. This paper discusses the adaptation of a high dimensional solution space and proposes a possible approach to it. A Visualisation induced Self Organising Map (Vi...

We introduce a novel two-stage automatic XML mark-up system, which combines the WEBSOM approach to document categorisation in conjunction with the C5 inductive learning algorithm. The WEBSOM method clusters the XML marked-up documents such that semantically similar documents lie close together on a Self-Organising Map (SOM). The C5 algorithm automatically learns and applies mark-up rules derive...

In this paper an application of the TS-SOM variant of the self-organising map algorithm on the problem of copyright theft detection for bitmap images is shown. The algorithm facilitates the location of originals of copied, damaged or modified images within a database of hundreds of thousands of stock images. The method is shown to outperform binary decision tree indexing with invariant frame de...