Colour quantisation technique based on image decomposition and its embedded system implementation

Abstract

A new colour quantisation (CQ) technique and its corresponding embedded system realisation are introduced. The CQ technique is based on image split into sub-images and the use of Kohonen self-organised neural network classifiers (SONNC). Initially, the dominant colours of each sub-image are extracted through SONNCs and then are used for the quantisation of the colours of the entire image. The proposed CQ technique can use both colour components and spatial features, achieving better approximation of the final image to the spatial characteristics of the original one. In addition, for the estimation of the proper number of dominant image colours, a new algorithm based on the projection of the image colours into the first two principal components is proposed. The image split into sub-images offers reduction of the on-chip memory requirements and is suitable for embedded system (or system-on-chip) implementation of the most timeconsuming part of the technique. Applying a systematic design methodology to the developed CQ algorithm, an efficient embedded architecture based on the ARM7 processor achieving high-speed processing and less energy consumption, is derived.

Color quantization for image processing using self information

“…For instance, [6] and [7] propose to integrate local color features and rely on unsupervised learning to extract optimal color prototypes. Classes are then handled by a split and merge process.…”

“…The inclusion of spatial features brings visually very good results. While the implementations proposed in [6] and [7] significantly improve computational efficiency as compared to other clustering based approaches, the resulting algorithm remains quite complex.…”

Real-Time Image and Video Processing: From Research to Reality

“…Of course, the developments in industrial inspection [25,34,67,135,147] and medical imaging systems [18,23,24,44,136,143,145] will continue to progress. The use of color image data [8,85,107,109], or in some cases, multispectral image data [139] in real-time image/video processing systems is also becoming an important area of research.…”

An Innovative Algorithm for Solving Jigsaw Puzzles Using Geometrical and Color Features

“…In the second stage of the technique, a Kohonen's SOFM based color reduction method proposed by Papamarkos et al [8]- [10] is applied. The metric that uses Kohonen SOFM is the Euclidian color distance.…”

“…The other one has to do with color segmentation. Color segmentation is being accomplished by a Kohonen's SOFM (Self Organized Feature Map) based technique proposed by Papamarkos et al [8]- [10]. In the second phase we examine all the pieces in pairs.…”