• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.835-838
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• 2000

Popular methods for extracting a text region in video images are in general based on analysis of a whole image such as merge and split method, and comparison of two frames. Thus, they take long computing time due to the use of a whole image. Therefore, this paper suggests the faster method of extracting a text region without processing a whole image. The proposed method uses line sampling methods, FFT and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 92% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image, and fast skipping of the images that do not contain a text.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.247-253
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• 2003

The mainly used technique to correct satellite images with geometric distortion is to develop a mathematical relationship between pixels on the image and corresponding points on the ground. Polynomial models with various transformations have been designed for defining the relationship between two coordinate systems. GCP based geometric correction has peformed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The Region with highly variant height is rectified with distortion on overall plane mapping. To consider locally variable region in satellite image, TIN-based rectification on a satellite image is proposed in this paper. This paper describes the relationship between GCP distribution and rectification model through experimental result and analysis about each rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.401-402
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• 2019

The purpose of this study is to find specific service quality factors of enterprises that can maximize the perception of banks' services to users of commercial banks in China, and to establish empirically how these quality factors affect the bank's image. They also want to verify the impact of the positive image of the bank on the user's satisfaction and the willingness to use the bank's services. For empirical verification of this study, questionnaires will be used to customers who have used the services of each of the four commercial banks in China, and the survey was conducted. The collected data were analyzed using the SPSS using statistical techniques such as Cronbach' ${\alpha}$, Investigative Factor Analysis, Reliability Analysis, Correlation Analysis, Regression and Difference Verification. The results of the verification were summarized below. First, the quality of service of commercial banks has a partial positive effect on the bank's image. Second, the image of a commercial bank has a positive effect on customer satisfaction. Third, the image of a commercial bank has a positive effect on the purpose of use. Fourth, the image of commercial banks has a partial mediated effect between service quality and customer satisfaction. Fifth, the image of a commercial bank has a partial mediated effect between the quality of service and its intended use.

• Journal of Oral Medicine and Pain
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• v.21 no.2
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• pp.255-264
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• 1996

This study was performed to demonstrate the method of image reformation for dental implants, using a personal computer with inexpensive softwares and to compare the images reformatted using the above method with those using Dentascan software. CT axial slices of 4 mandibles of 4 volunteers from GE Highspeed Advantage(GE Medical systems, U.S.A.) were used. personal computer used for image reformation was PowerWave 604/120 (Power computing Co, U.S.A. ) and softwares used were Osiris (Univ. Hospital of Geneva, Switzerland) and ImportACLESS Vl.1 (Designed Access Co., U.S.A.) for importing CT images and NIH image 1.58 (NIH, U.S.A.) for image processing. Seven image were selected among the serial reconstructed cross-sectional images produced by Dentascan. Seven resliced cross-sectional images at the same position were obtained at the personal computer. Regression analysis of the measurements of PC group was done against those of DS group. Measurements of the bone height and width at the reformer cross-sectional images using Mac-compatible computer was highly correlated with those using workstation with Dentascan software(height : r2= 0.999, p<0.001, width : r2= 0.993, p <0.001). So, it is considered that we can use a personal computer with inexpensive software for the dental implant planning, instead of the expensive software and workstation.

• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.174-179
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• 2006

In this paper we present a text detection method inspired by wavelet packet analysis and improved fuzzy clustering algorithm(IAFC).This approach assumes that the text and non-text regions are considered as two different texture regions. The text detection is achieved by using wavelet packet analysis as a feature analysis. The wavelet packet analysis is a method of wavelet decomposition that offers a richer range of possibilities for document image. From these multi scale features, we adapt the improved fuzzy clustering algorithm based on the unsupervised learning rule. The results show that our text detection method is effective for document images scanned from newspapers and journals.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.370-384
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• 2017

The image segmentation is the most important operation in an image processing system. It is located at the joint between the processing and analysis of the images. Unsupervised segmentation aims to automatically separate the image into natural clusters. However, because of its complexity several methods have been proposed, specifically methods of optimization. In our work we are interested to the technique SFLA (Shuffled Frog-Leaping Algorithm). It's a memetic meta-heuristic algorithm that is based on frog populations in nature searching for food. This paper proposes a new approach of unsupervised image segmentation based on SFLA method. It is implemented and applied to different types of images. To validate the performances of our approach, we performed experiments which were compared to the method of K-means.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.47-58
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• 2018

In this paper, we propose a method for skin condition analysis using a camera module embedded in a smartphone without a separate skin diagnosis device. The type of skin disease detected in facial image taken by smartphone is acne, pigmentation, blemish and flush. Face features and regions were detected using Haar features, and skin regions were detected using YCbCr and HSV color models. Acne and flush were extracted by setting the range of a component image hue, and pigmentation was calculated by calculating the factor between the minimum and maximum value of the corresponding skin pixel in the component image R. Blemish was detected on the basis of adaptive thresholds in gray scale level images. As a result of the experiment, the proposed skin condition analysis showed that skin diseases of acne, pigmentation, blemish and flush were effectively detected.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• KSTLE International Journal
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• v.3 no.1
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• pp.54-59
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• 2002

It can be effective on failure diagnosis of oil-lubricated tribological system to analyze operating conditions with morphological characteristics of wear debris in a lubricated machine. And it can be recognized that results are processed threshold images of wear debris. But it is needed to analyse and identify a morphology of wear debris in order to predict and estimate a operating condition of the lubricated machine. If the morphological characteristics of wear debris are identified by the computer image analysis and the neural network, it is possible to recognize the friction condition. In this study, wear debris in the lubricating oil are extracted from membrane filter (0.45 ${\mu}m$) and the quantitative value fur shape parameters of wear debris was calculated through the computer image processing. Four shape parameters were investigated and friction condition was recognized very well by the neural network.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.877-878
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• 2006

In this paper, we propose a skin lesion detection to develop the system of fluorescence image analysis to identify the fluorescence of topical methyl aminolevulinate(MAL) idduced PpIX in patients with BCC accurately. By fluorescence image analysis we define the border between tumo and tumor-free areas on fluorescence image after topical application of MAL ointment. We excised both the tumor and peri-tumoral areas widely from the 10 patients with BCC, and divided tissue samples into 3 area, such as tumor area, suspected tumor area, tumor-free area, respectively. Our proposed method migt play a role as an adjunctive tool to define the border between tumor and tumor-free areas for Mohs' micrographic surgery.