Nam-Chul Kim

Mitome: dynamic and interactive database for comparative mitochondrial genomics in metazoan animals

Mitome is a specialized mitochondrial genome database designed for easy comparative analysis of various features of metazoan mitochondrial genomes such as base frequency, A+T skew, codon usage and gene arrangement pattern. A particular function of the database is the automatic reconstruction of phylogenetic relationships among metazoans selected by a user from a taxonomic tree menu based on nucleotide sequences, amino acid sequences or gene arrangement patterns. Mitome also enables us (i) to easily find the taxonomic positions of organisms of which complete mitochondrial genome sequences are publicly available; (ii) to acquire various metazoan mitochondrial genome characteristics through a graphical genome browser; (iii) to search for homology patterns in mitochondrial gene arrangements; (iv) to download nucleotide or amino acid sequences not only of an entire mitochondrial genome but also of each component; and (v) to find interesting references easily through links with PubMed. In order to provide users with a dynamic, responsive, interactive and faster web database, Mitome is constructed using two recently highlighted techniques, Ajax (Asynchronous JavaScript and XML) and Web Services. Mitome has the potential to become very useful in the fields of molecular phylogenetics and evolution and comparative organelle genomics. The database is available at: http://www.mitome.info.

Segmentation using a competitive learning neural network for image coding

This paper describes a practical segmentation procedure using a simple competitive learning neural network to yield a complete segmentation suitable for segmentation-based image coding. Image segmentation is considered as a vector quantization problem. The procedure using the FSCL neural network for the vector quantization has the two main parts: primary and secondary segmentation. In the primary segmentation, an input image is finely segmented by the FSCL. In the secondary segmentation, a lot of small regions and similar regions with larger size generated in the preceding step are eliminated or merged together by the FSCL which performs partitioning and learning every input vector. Experimental results show that the procedure described here yields the reconstructed image of reasonably acceptable quality even at the low bit rate of 0.25 bit/pel.

Real-time automatic target tracking based on spatio-temporal gradient method with generalized least square estimation

The result of a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is presented for the detection of an object motion in an image sequence corrupted by additive white noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).<<ETX>>

Conditional run-length coding for multilevel graphic image

The concept of conditional run-length coding mainly used for bilevel image is extended for multilevel graphic image. It is shown that the extended coding algorithm is also optimum for the Markov model. Its performance is compared with bit-plane coding and cosine transform coding.