• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.137-147
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• 1994

In this paper,we propose a knowledge-based system for locating Destination Address Block(DAB) by analyzing the structure of Korean envelope images. In the proposed system the preprocessing steps such as adaptive binarization connected component extraction and deskewing are carried out first for the effective structure analysis of the envelope image. Then DAB containing address name and zipcode parts of the input envelope image is extracted by an iterative procedure based on the knowledge acquired from the statistical feature analysis of the various envelope images. Most of the system for slocating address blocks on envelopes have extracted DAB by segmenting an envelope image into several candidate blocks followed by selecting one among the candidate blocks. Because it is very difficult to segment a Korean envelope image into several blocks due to the specific writing habits that the addresses on the envelope are written in close proximity to each other the proposed iterative procedure determines DAB by splitting or merging the connected components and verifies the determined DAB without segmentation and selection. Experiments with a great number of the live envelopes provided from Seoul Mail Center in Koorea were carried out. The results reveal that the proposed system is very effective for address block location on Korean envelopes.

• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.1 s.120
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• pp.59-68
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• 2007

This article statistically analyzed contributive levels of district image based on an effect and a similarity index through the evaluation of citizens and suggested the efficient management system of a city image according to the results. For this study, Busan City was selected as a case city by the preceding literature and was investigated concerning district image and city image through a questionnaire. The new evaluation method for analysis of a city image was presented in this process. The results of this research are as follows: 1. Busan City has a substantial positive and culturally unique image, and each of its districts have other image characteristics. for example, the CBD district has a positive image, and the sea shore district has a busy and prosperous image, but the backward sea shore district has an image of stagnancy. 2. The image of Yeonje-gu has the largest effect on the image of Busan. Next in influence are Jung-gu, Saha-gu, Suyoung-gu, respectively. The effect index is closely connected with the variance of evaluative adjectives. 3. Busanjin-gu and Haeundae-gu have similar images to Busan City. Next in similarity are Nam-gu, Jung-gu, Youngdo-gu, Suyoung-gu, respectively. The similarity index is closely connected with the correlation of evaluative adjectives. Busan City and its districts can establish their image strategies with the above analyzed results. This study is meaningful in that a statistical evaluative method was proposed. With continued follow-up research, this study may serve as a systematic and logical model to improve the urban landscape and image.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.203-208
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• 2015

Image degradation will occur depending on hardware characteristics according to the lapse of time between beam projectors when multivision system is installed in the Theme park/Exhibition/Science Museum. In this paper, we have researched the 10-bit High-depth and high-resolution $360^{\circ}$ projection image analysis technique to solve the problems of quality and the maintenance of the theater. The goal is to minimize the economic losses and the development of special theater calibration system that can efficiently support a quality of an image. We proposed the method of image analysis technology, and explained the detailed functions and evaluation methods for image analysis technique. Evaluation method included the performance items, and proposed reasonable value to the experimental method and the goal value.

• Proceedings of the KSRS Conference
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• v.1
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• pp.282-285
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• 2006

This paper analyzed the characteristics of the Lossy JPEG of the meteorological satellite image, and analyzed the quality of the Lossy JPEG compression, which is proper for the LRIT(Low Rate Information Transmission) to be serviced to the SDUS(Small-scale Data Utilization Station) system of the COMS(Communication, Oceans, Meteorological Satellite). Since COMS is to start running after 2008, we collected the data of the MTSAT-1R(Multi-functional Transport Satellite -1R) for analysis, and after forming the original image to be used to LRIT by each channel and time zone of the satellite image data, we set the different quality with the Lossy JPEG compression, and compressed the original data. For the characteristic analysis of the Lossy JPEG, we measured PSNR(Peak Signal to Noise Rate), compression rate and the time spent in compression following each quality of Lossy JPEG compression. As a result of the analysis of the satellite image data of the MTSAT-1R, the ideal quality of the Lossy JPEG compression was found to be 90% in the VIS Channel, 85% in the IR1 Channel, 80% in the IR2 Channel, 90% in the IR3 Channel and 90% in the IR4 Channel.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.44-49
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• 2003

The morphological analysis of wear debris can provide early a failure diagnosis in lubricated moving system. It can be effective to analyze operating conditions of oil-lubricated tribological system with shape characteristics of wear debris in a lubricant. But, in order to predict and recognize an operating condition of lubricated machine, it is needed to analyze and to identify shape characteristics of wear debris. Therefore, If the morphological characteristics of wear debris are recognized by computer image analysis using the neural network algorithm, it is possible to recognize operating condition of hydraulic driving members. In this study, wear debris in the lubricating oil are extracted by membrane filter (0.45$\mu\textrm{m}$), and the quantitative values of shape parameters of wear debris are calculated by the digital image processing. This shape parameters are studied and identified by the artificial neural network algorithm. The result of study could be applied to prediction and to recognition of the operating condition of hydraulic driving members in lubricated machine systems.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.318-322
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• 1997

A prototype of combustion zone monitoring system as been developed and installed into tuyeres of the blast furnace. The system consists of CCD(charge coupled device) cameras, sonic flow meters, an image processor and a personal computer. The personal computer collects raceway luminance data and operational data from the image processor that is connected to the color CCD camera from the blast furnace process computer, respectively. In addition, the sonic flow meters supply coal injection rate data to the personal computer. Then, the personal computer evaluates the combustion conditions with the raceway inspection algorithm. This integrated monitoring system allows us to detect abnormal raceway conditions and the clogging status of coal injection pipe. The image processing techniques of the system enable us to effectively monitor unburnt coal sticking to tuyere tip and injection lance wear conditions. Such a developed system ensures rapid and precise raceway inspection. The image processing capability of the system has helped operator to early detect both the unburnt coal sticking problem and the errosion problem of injection lance. Furthermore, the system could control the abnormal raceway condition based the the analysis results obtained from combustion monitoring.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.3 s.30
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• pp.61-67
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• 2004

Satellite and aerial images are effectively used to monitor ecological and environmental situation. More and more officials in the Ministry of Environment thus need to utilize these image data for various administrative affairs. However, it is difficult not only to deliver to the officials these image data mostly of large capacity through network but also for them to actively use the delivered data without specialized knowledge in remote sensing and image processing. Therefore, we established a large rapacity image data service system employing image compressive transmission and web-based image processing techniques. This system allows the officials to rapidly access all the associated image data and conveniently utilize the data using various functions implemented for remote sensing, image processing, GIS operations. Consequently, this system have been actively utilized for the decision making processes of the officials and hence accomplished a great reduction in the resources required for the data analysis for various administrative affairs.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.170-173
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• 2001

To apply stereo vision system to obstacle recognition system of AGV, we constructed algorithm of stereo matching and distance measuring with stereo image for positioning of object in area. And using this system, we look into the error between real position and measured position, and studied relationship of compensation.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.1-10
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• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.415-433
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• 1998

Digora system is an intraoral indirect digital radiography system utilizing storage phosphor image plate. It has wide dynamic range which allows it to decrease the patient s exposure time and may increase diagnostic ability through image processing (such as edge enhancement, grey scale conversion, brightness change, and contrast enhancement). And also, it can transmit and storage image information. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries between Conventional radiograph and Digora images(unenhanced image, brightness & contrast controlled image, and edge enhanced image). ROC(Receiver Operating Characteristic) analysis, paired t-tests, and F-tests were done for the statistical evaluation of detectability. The following results were acquired: 1. In Grade I lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.953, 0.933, 0.965, 0.978 (p>0.05). 2. In Grade II lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.969, 0.964, 0.988, 0.994. Among theses areas, there was just statistical significance between Diagnostic abilities of Digora edge enhanced image and Conventional radiograph (p<0.05). 3. In the Interobserver variability, the ROC curve areas of Digora edge enhanced image was lowermost in these areas, regardless of the Carious lesion depths. In conclusion, intraoral indirect digital system, Digora system, has the potential possibility as an alternative of Conventional radiograph in the diagnosis of proximal caries.