Jari Kangas

Tampere University, School of Information Sciences, Post-Doc

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Papers by Jari Kangas

Sample Weighting When Training Self-Organizing Maps For Image Compression

| Image compression is an essential task for image storage and transmission applications. Vector ... more | Image compression is an essential task for image storage and transmission applications. Vector quantization is often used when high compression rates are needed. Self-Organizing Map (SOM) algorithm can be used to generate codebooks for vector quantization. Previously it has been demonstrated that using the special property of the SOM algorithm that the codebook entries are ordered one can use prediction coding of codewords to make the compression more e ective. In this paper it is shown that training the SOM algorithm by using di erent weighting for sample blocks having di erent statistical characteristics one can further increase the compression e ciency.

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Increasing the Error Tolerance in Transmission of Vector Quantized Images by Self-Organizing Map

Image compression is needed for image storage and transmission applications.

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Transient map method in stop consonant discrimination

... Map method has also been used in Japanese tests for more thorough classification of nasals /m... more

<title>Color clustering and its application in character location</title>

Second International Conference on Image and Graphics, 2002

ABSTRACT In this paper, a normalized RGB space based color clustering method is given, and furthe... more ABSTRACT In this paper, a normalized RGB space based color clustering method is given, and further the application of color clutering in character location is described. Color clustering is used to group a color image into the different binary layers. During color clustering, the normalized RGB space is adopted. In each layer, its color should be homogeneous. As characters normally have different information in color from their background, characters and their background are grouped into different color layers, which are fairly useful to locate characters. In order to achieve character location, an aligning and merging analysis (AMA) scheme is presented to locate all potential characters on each color layer. The experimental results have proven the effectiveness of the method, which is one important part of the optical character recognition (OCR) system.

Time-Dependent Self-Organizing Maps for Speech Recognition

Artificial Neural Networks, 1991

$Research paper thumbnail of Soinnittomien klusiilien erottelu {O} taniemen Pu\-heen\-tun\-nis\-tus\-j {\"{a}} r\-jes\-tel\-m {\"{a}} s\-s {\"{a}}({C} lassification of Voiceless Stop Consonants in {O} taniemi {S} peech {R} ecognition {S} ystem)$

Soinnittomien klusiilien erottelu {O} taniemen Pu\-heen\-tun\-nis\-tus\-j {\"{a}} r\-jes\-tel\-m {\"{a}} s\-s {\"{a}}({C} lassification of Voiceless Stop Consonants in {O} taniemi {S} peech {R} ecognition {S} ystem)

Using transient maps in classification of voiceless stop consonants

Self-organizing maps in error tolerant transmission of vector quantized images

Character-like region verification for extracting text in scene images

This paper proposes a method of identifying character-like regions in order to extract and recogn... more This paper proposes a method of identifying character-like regions in order to extract and recognize characters in natural color scene images automatically. After connected component extraction based on a multi-group decomposition scheme, alignment analysis is used to check the block candidates, namely, the character-like regions in each binary image layer and the final composed image. Priority adaptive segmentation (PAS) is

Using {S} elf-{O} rganizing {M} ap in Error Tolerant Transmission of Vector Quantized Images

Prototype search for a nearest neighbor classifier by a genetic algorithm

This paper deals with the problem of finding good prototypes for a condensed nearest neighbor cla... more This paper deals with the problem of finding good prototypes for a condensed nearest neighbor classifier for a character recognition system based on directional codes. A prototype search by a genetic algorithm capable of creating new prototypes is compared against a direct prototype selection algorithm. It is shown in a leave-one-out experiment that the prototypes found by a genetic algorithm give significantly smaller intraclass distances to class members, and significantly larger normalized interclass distances.

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Transient map method in stop consonant discrimination

... Map method has also been used in Japanese tests for more thorough classification of nasals /m... more

3043 works that have been based on the self-organizing map (SOM) method developed by Kohonen

Increasing the error tolerance in transmission of vector quantized images by selforganizing map

Image compression is needed for image storage and transmission applications.

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Temporal knowledge in locations of activations in a self-organizing map

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Gesture Based Document Editor

Status Report Of The Finnish Phonetic Typewriter Project

by Jari Kangas and Kari Torkkola

Icann, 1991

In connection to a speech recognizer, the aim of which is to produce phonemic transcriptions of a... more In connection to a speech recognizer, the aim of which is to produce phonemic transcriptions of arbitrary spoken utterances, we investigate the combined e ect of several improvements at di erent stages of phoneme recognition. The core of the basic recognition system is Learning Vector Quantization (LVQ1) 1]. This algorithm was originally used to classify FFT-based short-time feature vectors into phonemic classes. The phonemic decoding stage was earlier based on simple durational rules 2] 3]. At the feature level, we now study the e ect of using mel-scale cepstral features and concatenating consecutive feature vectors to include context. At the output of vector quantization, a comparison of three approaches to take into account the classi cations of feature vectors in local context is presented. The rule-based phonemic decoding is compared to decoding employing Hidden Markov Models (HMMs). As earlier, an optional grammatical post-correction method (DEC) is applied. Experiments conducted with three male speakers indicate that it is possible to increase signi cantly the phonemic transcription accuracy of the previous conguration. By using appropriately liftered cepstra, concatenating three adjacent feature vectors, and using HMM-based phonemic decoding, the error rate can be decreased from 14.0 % to 5.8 %.

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LVQPAK: A software package for the correct application of Learning Vector Quantization algorithms

by Jari Kangas and Kari Torkkola

[Proceedings 1992] IJCNN International Joint Conference on Neural Networks, 1992

This paper is an overview of the program package LVQ PAK, which has been developed for convenient... more This paper is an overview of the program package LVQ PAK, which has been developed for convenient and e ective application of Learning Vector Quantization algorithms. Two new features are included: fast con ict-free initial distribution of codebook vectors into the class zones, and the optimized-learning-rate algorithm OLVQ1.

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A voice activated typewriter based on phonemes

by Jari Kangas and Kari Torkkola

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