• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.10
• /
• pp.1109-1116
• /
• 1992

Mathematical morphology, theoretical foundation for morphological filter, is very efficient for the analysis of the geometrical characteristics of signals and systems and is used as a predominant tool for smoothing the data with noise. In this study, H/W design of morphological filter is implemented to process the gray scale dilation and the erosion in the same circuit and to choose the maximum and minimum value by a selector, resulting in their education of the complexity of the circuit and an architecture for parallel processing. The structure of morphological filter consists of the structuring-element block, the image data block, the control block, the ADD block, the MIN/MAX block, etc, and is designed on an one-chip for real time operation.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.3
• /
• pp.390-394
• /
• 2003

To classify the significant wavelet coefficients into edge area and noise area, a morphological clustering filter applied to wavelet shrinkage is introduced. New methods for wavelet shrinkage using morphological clustering filter are used in noise removal, and the performance is evaluated under various noise conditions.

• Journal of the Korean Institute of Navigation
• /
• v.20 no.4
• /
• pp.99-109
• /
• 1996

Though median filter is used for removing noise and smoothing image. But, the result of it has distortion around edge. And then, this paper proposes new noise removing algorithm by recursive morphological processing. Basic operation is same each other, but there is some different processing method between recursive morphology and general morphology theory. This recursive morphological filter can be viewed as the weighted order static filter, and then it has a weighted SE(structuring element). Especially using this algorithm to remove the 10% gaussian noise, this paper confirmed that PSNR is improved about 0.642~1.5757 db reserving edge well better than the results of the traditional median filter.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.283-287
• /
• 1993

We constructed morphological filter for single sweep records of event-related potential (ERP), especially P300 waveform. By combining 4 basic operations; erosion, dilation, opening and closing, we can derive any desired filters whose property fits the current objectives. The morphological filter for single sweep records of ERP was constructed by taking account of the features of the signal and noise components. The morphological filter has superior properties of separating the signal ancl the noise even existing within a same frequency band. The constructed morphological filter was tested by using simulation data of ERP and then applied to actual ERP data of a normal subject. The results proved that the constructed morphological filter was an appropriate tool for single sweep records of ERP.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.11
• /
• pp.1264-1270
• /
• 1992

MF(Morphological filter) is generally composed of several morphological operation, which are the diverse structuring element. The two basic operation are erosion and dilation. The two other operation, opening and closing, are defined based on these two operation. Performance of open-closing(OC) is better exellent than close-opening(CO) to reduce noise of image data with Gaussian noise. In this paper, to use the hybrid median filter in processing the image, is shown that hybrid median filter has better results image quality than other filters, to analyze by computer simulation.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.95-98
• /
• 2001

Edge detection is an important problem in computer vision and image understanding. Because the threshold is difficult to properly determine, edge images gained by the usually gradient-based segmentation methods are often tend to have many disjoint or overlapping boundaries, which makes the edge images spinous. In this paper, a practical multilevel morphological filter is presented for smoothing spinous edge images. The experimental results show that the method is effective in dealing with the images of a target in the sky.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.9 no.3
• /
• pp.172-177
• /
• 2009

In this paper, a new morphology-based homomorphic filtering technique is presented to enhance features in medical images. The homomorphic filtering is performed based on the morphological sub-bands, in which an image is morphologically decomposed. An evolutionary design is carried to find an optimal gain and structuring element of each sub-band. As a search algorithm, Differential Evolution scheme is utilized. Simulations show that the proposed filter improves the contrast of the interest feature in medical images.

• KIEE International Transaction on Systems and Control
• /
• v.2D no.2
• /
• pp.115-119
• /
• 2002

In this paper we present a generalized directional morphological filtering algorithm for the removal of impulse noise, which is based on a combination of impulse noise detection and a weighted rank-order morphological filtering technique. For salt (or pepper) noise suppression, the generalized directional opening (or closing) filtering of the input signal is selectively used. The detection of impulse noise can be done by the geometrical difference of opening and closing filtering. Simulations show that this new filter has better detail feature preservation with effective noise reduction compared to other nonlinear filtering techniques.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1752-1757
• /
• 1991

This paper presents a new method for detecting microcalcifications on mammograms by using morphological filter. This filter is an extension of Top-hat transformation in morphological operations with multi-scale and multiple structuring elements. The proposed method makes it possible to detect geometrical structures considered to be microcalcifications on the basis of their size, shape and density. Experimental results to show the effectiveness of the proposed method are also presented.

• Journal of information and communication convergence engineering
• /
• v.12 no.1
• /
• pp.60-65
• /
• 2014

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.