• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.509-516
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• 2002

This paper proposes an efficient algorithm which recognizes the mixed document image consisting of the images, texts, tables, and straight lines. This system is composed of three steps. The first step is the detection of rotation angle for complementing skewed images, the second is detection of erasing an unnecessary background region and last is the classification of each component included in document images. This algorithm performs preprocessing of detecting rotation angles and correcting documents based on the detected rotation angles in order to minimize the error rate by skewness of the documentation. We detected the rotation angie using only horizontal and vertical components in document images and minimized calculation time by erasing unnecessary background region in the detecting process of component of document. In the next step, we classify various components such as image, text, table and line area included in document images. we applied this method to various document images in order to evaluate the performance of document recognition system and show the successful experimental results.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.377-384
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• 2009

A new algorithm in order to classify various contents in the image documents, such as text, figure, graph, table, etc. is proposed in this paper by classifying contents using texture-based PCA, and by segmenting document images using local entropy-based histogram. Local entropy and histogram made the binarization of image document not only robust to various transformation and noise, but also easy and less time-consuming. And texture-based PCA algorithm for each segmented region was taken notice of each content in the image documents having different texture information. Through this, it was not necessary to establish any pre-defined structural information, and advantages were found from the fact of fast and efficient classification. The result demonstrated that the proposed method had shown better performances of segmentation and classification for various images, and is also found superior to previous methods by its efficiency.

• Journal of KIISE
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• v.43 no.7
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• pp.795-800
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• 2016

In image classification, recent CNNs compete with human performance. However, there are limitations in more general recognition. Herein we deal with indoor images that contain too much information to be directly processed and require information reduction before recognition. To reduce the amount of data processing, typically variational inference or variational Bayesian methods are suggested for object detection. However, these methods suffer from the difficulty of marginalizing over the given space. In this study, we propose an image-text integrated recognition system using active vision based on Spatial Transformer Networks. The system attempts to efficiently sample a partial region of a given image for a given language information. Our experimental results demonstrate a significant improvement over traditional approaches. We also discuss the results of qualitative analysis of sampled images, model characteristics, and its limitations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1131-1146
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• 1992

In this paper, we suggest a new algorithm applied to the segmentation of published documents to obtain constituent and layout information of document. Firstly, we begin the process of blocking and labeling on a 300dpi scanned document. Secondly, we classify the blocked document by individual sub-regions. Thirdly, we group sub-regions into graphic areas and text areas. Finally, we extract information for layout recognition by using the data. From an experiment on papers of an academic society, we obtain the above 98% of region classification rate and extraction rate of information for the layout recognition.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.578-589
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• 2014

Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.

• Korean Journal of Medicinal Crop Science
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• v.19 no.1
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• pp.24-30
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• 2011

This text was analyzed and investigated the vegetation and floristic composition by cluster analysis and classification of phytosociological method, to evaluate the species composition, habitat environment and community structure of Liriope platyphylla and Liriope spicata group in Korea. The southeast slope gradient of the habitat of L. platyphylla and L. spicata was 6.7 to 8.4%, and the habitat altitude of L. platyphylla (41.0 m), L. spicata (114.9 m) was different. Habitat distribution of L. spicata was broader than L. platyphylla. Appearing plants of L. platyphylla and L. spicata group was 58 taxa, 99 taxa, respectively, and Coverage of tree layer was 87.5%, 92.5% respectively. In genus Liriope group, the highest appearing frequency of plant grow in the moist valley as Quercus serrata. Thus, plants of genus Liriope growth was better in moist shade. The vegetation of L. platyphylla group was classified into Quercus serrata community, Castanopsis sieboldii community, Pinus densiflora community and Pinus thunbergii community, and the Liriope spicata group was classified into Quercus serrata community, Quercus alien community, Quercus acutissima community, Prunus verecunda community, Robinia pseudoacacia community, Pinus densiflora community and Pinus thunbergii community. In genus Liriope group, Quercus serrata and Pinus densiflora communities was the closest the similarities.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• The Journal of Korean society of community based occupational therapy
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• v.6 no.1
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• pp.49-60
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• 2016

Objective : By organizing systematically the study case that use Robot Therapy as intervention tool according to PICO (Patient, Intervention, Comparison, Outcome), This study aims to investigate the domestic Robot Therapy's present condition. Methods : We searched 710 pieces of domestic scientific journal and master's thesis during the past nine years in 'Research Information Sharing Service' and 'National Digital Science Library' database using the keyword 'Robot therapy'. We finally chose 15 pieces of domestic scientific journal and master's thesis among the domestic studies that based on the full text which is affordable and used robot by therapeutic intervention tool. Chosen studies were layed out by PICO that could organize the resources systematically. Results : The quality of study tool was used to the method of evidence-based study level of 5 step classification. More than three stages of quality level study was 13. Result of dividing the studies using robot therapy by intervention field, language, lower extremity(gait), cognition, development and study for the region of the upper extremity of five is advancing. Conclusion : Nationally, the robot therapy has been used in various area that include the upper extremity and lower extremity's intervention of language, cognition, growth and others. We hope that this study for baseline data will be utilized in various area engaging to domestic robot therapy.