• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.209-213
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• 2002

MRA(Multi-resolution analysis) algorithm by Wavelet and morphology with $3{\times}3$ SQ(square) SE(structure element) is efficient to remove ship's radar clutter progressively and enhances detecting performance. Smoothing efficiency of RMM (Recursive mathematical Morphology) is better than that of Morphology. So, to get a better result than that of old algorithms, this paper proposes a new MRA algorithm which uses Wavelet and Recursive mathematical Morphology with $3{\times}3$ RHR(rhombus) SE. Simulation result of the proposed algorithm shows that PSNR is 0.65~1.50db better than that of old method.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.39-48
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• 2006

This paper is proposed the wavelet morphology algorithm with the spatial auto-object segmentation concept and the clustering concept. When it is segmented the color face by using the proposed algorithm, it is made to the simple image. Also, it is used the spatial quality in order to segment and detect the image as a real time without the user's manufacturing. This removed a small part that is regarded as a noise in image by HSV color model and applied the wavelet morphology to remove a part excepting for the face image. In this paper, it is made a comparison between the wavelet morphology algorithm and the morphology algorithm. And It is showed to accurately detect the face object parts in the image appled to HSV color space model.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.107-117
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• 2014

This paper proposed the method of removing baseline drift by eliminating local maxima such as P, R, T-wave signal region and local minima Q, S-wave signal region. We applied morphology-pair operations improved from morphology operation to the ECG signal. To eliminate overshoot in the result of morphology-pair operation, we apply median value operation to the result of morphology-pair operation. We use MIT/BIH database to estimate the proposed algorithm. Experiment result show that proposed algorithm removing baseline drift effectively without orignal ECG signal distortion.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.1
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• pp.19-27
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• 2007

In this paper, we develope and implement a TFT-LCD cell defects detection algorithm using morphology. To detect the bright line or dark line defects and the bright pixel or dark pixel defects of the TFT-LCD cells, we determine the shape of the morphology operators considering the shape characteristics of the TFT-LCD sub pixels. Using dilation, erosion, and the subtraction operators, we extract gray level defects information. Then, we apply the optimal threshold method which shows the best results in terms of several criteria. Finally, we determine the defects using labelling method. From various experiments using TFT-LCD panels, the proposed algorithm shows superior results.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.104-111
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• 1997

It is known as a difficult problem to recognize text-background mixed documents. In this paper a new string extraction algorithm, using mathematical morphology for the document consisting of text and overlapped periodic background pattern, is proposed. The algorithm consists of pattern periodicity feature extraction and background removal. The extracted pattern periodicity feature is used to determine the shape of structuring elements for morphological pre- and post-processing to remove background. The effectiveness of the proposed algorithm over the existing one is also verified through the experiments with various test documents.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.17-22
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• 2013

In this paper, we propose a concrete crack detection method using shape properties. It is based on morphology algorithm and crack features. We assume that an input image is contaminated by various noises. Thus, we use a morphology operator and extract patterns of crack. It segments cracks and background using opening and closing operations. Morphology based segmentation is better than existing integration methods using subtraction in detecting a crack it has small width. Also, it is robust to noisy environment. The proposed algorithm classifies the segmented image into crack and background using shape properties of crack. This method calculates values of properties such as the number of pixels and the maximum length of the segmented region. Also, pixel counts of clusters are considered. We decide whether the segmented region belongs to cracks according to those data. Experimental results show that our proposed crack detection method has better results than those by existing detection methods.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.53-62
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• 2007

In this paper, it can propose that Fuzzy Wavelet Morphology Neural Networks for the edge detection algorithm with being robustly a unclear boundary parts by brightness difference and being less sensitivity on direction to be detected the edges of images. This is applying the Fuzzy Wavelet Morphology Operator which can be simple the image robustly without the loss of data to DTCNN Structure for improving defect which carrys out a lot of operation complexly. Also, this color image can segment Y image with YCbCr space color model which has a lossless feature information of edge boundary sides effectively. This paper can offer the simulation of color images of 50ea for the performance verification of the proposal algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.142-148
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• 2004

In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1392-1394
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• 1996

This paper presents an algorithm to separate vowels from consonants in Korean characters captured in noisy images and to recognize them. The algorithm has been originally developed for the recognition of the usage code (which is represented by a single Korean character) in the license plates or Korean vehicles. It, however, could be easily adopted to other applications with minor changes, in which character recognition is needed and the environment is noisy. The key ideas or the algorithm are to localize the vowels utilizing the Hough transformation and to separate the vowels from consonants utilizing mathematical morphology. We observed that the presented algorithm effectively separates vowels even if the vowels and consonants are joined together after thresholding. We also observed that our algorithm outperforms some conventional algorithms especially when the input images are noisy. The details of the comparison study are presented in the paper.

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