• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.444-447
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• 2008

In this paper, we proposed the recognition system of car license plates to mitigate traffic problems. The processing sequence of the proposed algorithm is as follows. At first, a license plate segment is extracted from an acquired car image using morphological features and color information, and noises are eliminated from the extracted license plate segment using line scan algorithm and Grassfire algorithm, and then individual codes are extracted from the license plate segment using edge tracking algorithm. Finally the extracted individual codes are recognized by an FCM algorithm. In order to evaluate performance of segment extraction and code recognition of the proposed method, we used 100 car images for experiment. In the results, we could verify the proposed method is more effective and recognition performance is improved in comparison with conventional car license plate recognition methods.

• KSCI Review
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• v.14 no.2
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• pp.141-146
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• 2006

In this paper, we propose a new algorithm for recovering the broken letters of relics into an original form by using Z-map and image processing. The letters of relics may have been broken by a lot of rubbed copy and a long time and tide. They need to be restored. But the manual reconstruction is a very tedious and laborious task. Thus, it is necessary to automate the restoration process. This paper presents a realistic algorithm with an application to Tripitaka Koreana by using Z-map and morphological filter.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.8
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• pp.22-38
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• 1997

This paper proposes a new VLSI architecture for morphological filters and presents its chip design and implementation. The proposed architecture can significantly reduce hardware costs compared with existing architecture by using a feedback loop path to reuse partial results and a decoder/encoder pair to detect maximum/minimum values. In addition, the proposed architecture requires one common architecture for both diltion and erosion and fewer number of operations. Moreover, it can be easily extended for larger size morphologica operations. We developed VHDL (VHSIC hardware description language) models, performed logic synthesis using the SYNOPSYS CAD tool. We used the SOG (sea-of-gate) cell library and implemented the actual chip. The total number of gates is only 2,667 and the clock frequency is 30 MHz that meets real-time image processing requirements.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.102.2-102.2
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• 2011

Sunspots usually appear in a group which can be classified by certain morphological criteria. In this study we examine the moments which are statistical parameters computed by summing over every pixels of contours, in order to quantify the morphological characteristics of a sunspot group. The moments can be additional characteristics to the sunspot group classification such as McIntosh classification. We are developing a program for image processing, detection of contours and computation of the moments using continuum images from SOHO/MDI. We apply the program to count the sunspot numbers from 303 continuum images in 2003. The sunspot numbers obtained by the program are compared with those by SIDC. The comparison shows that they have a good correlation (r=89%). We are extending this application to automatic sunspot classification (e.g., McIntosh classification) and flare forecasting.

• Journal of Biomedical Engineering Research
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• v.17 no.1
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• pp.25-32
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• 1996

A new analytic method has been developed for the analysis of sperm morphology using Hough transform. This method is based on the characteristic that sperm heads have elliptic shape in addition to the density difference with the background Sperm heads are represented in elliptic form with five parameter, and the optimal parameters are estimated by iterative Hough transform. To reduce processing time practically, we restricted the transformed space in minimum volume and moved the searching volume to the maximum gradient for the estimated error. Morphological parameters were calculated from estimated sperm head boundaries without further processing.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.901-908
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• 2016

Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.

• Progress in Medical Physics
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• v.15 no.2
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• pp.70-76
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• 2004

The most important work for early detection of liver cancer and decision of its characteristic and location is good segmentation of a liver region from other abdominal organs. This paper proposes a fully automatic liver segmentation algorithm based on the abdominal morphology characteristic as an easy and efficient method. Multi-modal threshold as pre-processing is peformed and a spine is segmented for finding morphological coordinates of an abdomen. Then the liver region is extracted using C-class maximum a posteriori (MAP) decision and morphological filtering. In order to estimate results of the automatic segmented liver region, area error rate (AER) and correlation coefficients of rotational binary region projection matching (RBRPM) are utilized. Experimental results showed automatic liver segmentation obtained by the proposed algorithm provided strong similarity to manual liver segmentation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1419-1424
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• 1999

In order to implement morphological filters on image processing systems, the size of structuring element must be small due to the architectural constraints of the systems, which requires the decomposition of structuring element into small elements for the filters with large structuring elements. In this paper, an algorithm for decomposition of structuring element with no restriction on the shape and size is developed which enables sub-optimal implementation of any morphological filter on 3X3 pipeline machine. The given structuring element is first decomposed into the union of elements using sequential search procedure, then each element is further decomposed optimally into 3X3 elements, resulting in final sub-optimal 3$\times$3 hybrid decomposition. The proposed algorithm is applied to some structuring elements and the results close to the optimum are obtained.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1051-1058
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• 2018

This paper propose image processing algorithm to prevent safety accidents near by subway platform screen door(PSD). First, edges of the subway PSD images are detected and the boundary line between PSD and subway platform is detected to decide people's approach to the PSD using Hough transform. To do this, we draw the boundary line between the PSD and platform, to detect the boundary line and to decide the people's approach to the detected line is completely connected or not. Generally, edge is the basic characteristic of image; thus, edge detection is very important in image processing applications and computer vision area. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask, and morphological gradient from the structuring element of view and Canny edge detector are widely used. In this paper, we propose the detection algorithm about the people's approach to the subway PSD to prevent the safety accidents by using Canny edge detector and Hough transform and the computer simulation shows the results.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.625-635
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• 2005

In this paper, we propose a hybrid approach for segmenting the lungs efficiently and automatically in chest CT images. The proposed method consists of the following three steps. first, lungs and airways are extracted by two- and three-dimensional automatic seeded region growing and connected component labeling in low-resolution. Second, trachea and large airways are delineated from the lungs by two-dimensional morphological operations, and the left and right lungs are identified by connected component labeling in low-resolution. Third, smooth and accurate lung region borders are obtained by refinement based on image subtraction. In experiments, we evaluate our method in aspects of accuracy and efficiency using 10 chest CT images obtained from 5 patients. To evaluate the accuracy, we Present results comparing our automatic method to manually traced borders from radiologists. Experimental results show that proposed method which use connected component labeling in low-resolution reduce processing time by 31.4 seconds and maximum memory usage by 196.75 MB on average. Our method extracts lung surfaces efficiently and automatically without additional processing like hole-filling.