• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.102-108
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• 1999

It is important to decide processing unit in the large vocabulary speech recognition system we propose a Pseudo-Morpheme as the recognition unit to resolve the problems in the recognition systems using the phrase or the general morpheme. We implement a morphological analysis system and tagger for Pseudo-Morpheme. The speech processing system using this pseudo-morpheme can get better result than other systems using the phrase or the general morpheme. So, the quality of the whole spoken language translation system can be improved. The analysis-ratio of our implemented system is similar to the common morphological analysis systems.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1401-1408
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• 2011

This dissertation present a chip with Multi-Access Memory System(MAMS) and parallel processor for 16 Processing Elements of image processing purpose. MAMS is a kind of parallel access memory system and can simultaneously access to random pixel datas with eight types. It is possible to set a interval about pixel datas to access, too. The parallel processor built-in MAMS actually has been realized in 2003 but its performance fell short of a real time process for high-definition images. I designed a improved parallel processing system by means of addition and expansion of Memory Modules and Processing Elements of previous one. It is feasible to perform a Morphological Closing at the speed of 3 times of the previous one and 6 times of serial system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.5
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• pp.789-795
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• 2002

Color image is formed of combination of three color channels. Therefore its architecture is very complicated and it requires complicated image Processing for effective image segmentation. In this paper. we propose architecture of universalized Color Morphological Pyramids(CMP) which is able to give effective image segmentation. Image Pyramid architecture is a successive Image sequence whose area ratio $2^{\int}({\int}=1,2,....,N)$ after filtering and subsampling of input image. In this technique, noise removed by sequential filtering and resolution is degraded by downsampling using CMP in various color spaces. After that, new level images are constructed that apply formula using distance of neighbor vectors in close level images and segments its image. The feasibility of proposed method is examined by comparing with the results obtained from the existing method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.92-98
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• 2019

In this paper, we propose a deep learning system based on morphological neural network(MNN). The deep learning layers are morphological operation layer, pooling layer, ReLU layer, and the fully connected layer. The operations used in morphological layer are erosion, dilation, and edge detection, etc. Unlike CNN, the number of hidden layers and kernels applied to each layer is limited in MNN. Because of the reduction of processing time and utility of VLSI chip design, it is possible to apply MNN to various mobile embedded systems. MNN performs the edge and shape detection operations with a limited number of kernels. Through experiments using database images, it is confirmed that MNN can be used as a deep learning system and its performance.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.110-113
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• 1990

A new approach to impulsive noise rejection and background normalization of digitized electrocardiogram signals is presented using mathematical morphological operators that incoporate the shape information of a signal. A brief introduction to these nonlinear signal processing operators, as well as detailed description of the new algorithm, is presented. Empirical results show that the new algorithm has good performance in impulsive noise rejection and background normalization.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.577-582
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• 2002

The objective of this paper is to produce a weighted graph map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor circumstance. The AMR navigates in th unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. Then, the occupancy grid map is converted to a weighted graph map suing morphological image processing and thinning algorithms. the path- planning for autonomous navigation of a mobile robot can be carried out based on the occupancy grid map. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

• Proceedings of the KSRS Conference
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• v.2
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• pp.736-739
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• 2006

While hyperspectral data are very rich in information, their processing poses several challenges such as computational requirements, noise removal and relevant information extraction. In this paper, the application of advanced scale-space filtering to selected hyperspectral bands was investigated. In particular, a pre-processing tool, consisting of anisotropic diffusion and morphological leveling filtering, has been developed, aiming to an edge-preserving smoothing and simplification of hyperspectral data, procedures which are of fundamental importance during feature extraction and object detection. Two scale space parameters define the extent of image smoothing (anisotropic diffusion iterations) and image simplification (scale of morphological levelings). Experimental results demonstrated the effectiveness of the developed scale space filtering for the enhancement and smoothing of hyperspectral remote sensing data and their advantage against watershed over-segmentation problems and edge detection.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.10a
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• pp.115-123
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• 1998

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under different experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are shape fractal dimension and surface fractal dimension. The shape fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Tribology and Lubricants
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• v.18 no.2
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• pp.147-152
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• 2002

The morphological analysis of wear particle is a very effective means fur machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing. These descriptors to analyze shape and surface of wear particle are shape fractal dimension and surface fractal dimension. The boundary fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal parameter.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.53-58
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• 2001

Fractal dimension is the method to measure the roughness and the irregularity of something that cannot be defined obviously by Euclidean dimension. And the analysis method of this dimension don't need perfect, accurate boundary and color like analysis lot diameter, perimeter, aspect or reflectivity of wear particles or surface. If we arranged the morphological characteristic of various wear particle by using the characteristic of fractal dimension, it might be very efficient to the diagnosis of driving condition. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are boundary fractal dimension and surface fractal dimension.