• Title/Summary/Keyword: 이미지 등록

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Design and Implementation of Web Apps that Automatically Convert Floor Plan by Detecting Geometric Shapes (도형 검출을 통한 건축 평면도 자동 변환 웹앱 설계 및 구현)

  • Son, Dayeon;Kim, Doyeong;Shin, Dongho;Wang, Tae-su;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.225-228
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    • 2022
  • The method of calculating the architectural design cost of the Korean Society of Architecture Policy considers the time spent during the design period. Therefore, faster design times can reduce design costs. As a result of a survey of students majoring in architecture, they felt tiredness from repeated floor plan drawings and difficulties in that there were many things to consider when floor plan drawing. In this paper, we implement a program that can automatically convert sketches into standardized floor plans during the architectural design process and a web app for user convenience. In the proposed method, when a user registers a sketch image through a web app, the program separates the space in the drawing through geometric shapes detection. Based on the dimensions and spatial information shown in the sketch, the outer and inner walls are displayed and the appropriate furniture is placed in the space. Through the proposed method, the design cost can be expected to be reduced by reducing the time of the drawing process in the architectural design stage, and 95.2% of architectural students expressed their intention to use the program.

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The way to make training data for deep learning model to recognize keywords in product catalog image at E-commerce (온라인 쇼핑몰에서 상품 설명 이미지 내의 키워드 인식을 위한 딥러닝 훈련 데이터 자동 생성 방안)

  • Kim, Kitae;Oh, Wonseok;Lim, Geunwon;Cha, Eunwoo;Shin, Minyoung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.1-23
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    • 2018
  • From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

Semi-automated Tractography Analysis using a Allen Mouse Brain Atlas : Comparing DTI Acquisition between NEX and SNR (알렌 마우스 브레인 아틀라스를 이용한 반자동 신경섬유지도 분석 : 여기수와 신호대잡음비간의 DTI 획득 비교)

  • Im, Sang-Jin;Baek, Hyeon-Man
    • Journal of the Korean Society of Radiology
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    • v.14 no.2
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    • pp.157-168
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    • 2020
  • Advancements in segmentation methodology has made automatic segmentation of brain structures using structural images accurate and consistent. One method of automatic segmentation, which involves registering atlas information from template space to subject space, requires a high quality atlas with accurate boundaries for consistent segmentation. The Allen Mouse Brain Atlas, which has been widely accepted as a high quality reference of the mouse brain, has been used in various segmentations and can provide accurate coordinates and boundaries of mouse brain structures for tractography. Through probabilistic tractography, diffusion tensor images can be used to map comprehensive neuronal network of white matter pathways of the brain. Comparisons between neural networks of mouse and human brains showed that various clinical tests on mouse models were able to simulate disease pathology of human brains, increasing the importance of clinical mouse brain studies. However, differences between brain size of human and mouse brain has made it difficult to achieve the necessary image quality for analysis and the conditions for sufficient image quality such as a long scan time makes using live samples unrealistic. In order to secure a mouse brain image with a sufficient scan time, an Ex-vivo experiment of a mouse brain was conducted for this study. Using FSL, a tool for analyzing tensor images, we proposed a semi-automated segmentation and tractography analysis pipeline of the mouse brain and applied it to various mouse models. Also, in order to determine the useful signal-to-noise ratio of the diffusion tensor image acquired for the tractography analysis, images with various excitation numbers were compared.

Recognition of Passport Image Using Removing Noise Branches and Enhanced Fuzzy ART (잡영 가지 제거 알고리즘과 개선된 퍼지 ART를 이용한 여권 코드 인식)

  • Lee, Sang-Soo;Jang, Do-Won;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.377-382
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    • 2005
  • 본 논문에서는 출입국자 관리의 효율성과 체계적인 출입국 관리를 위하여 여권 코드를 자동으로 인식하는 방법을 제안한다. 여권 이미지는 기울어진 상태로 스캔 되어 획득되어질 수도 있으므로 기울기 보정은 문자 분할 및 인식에 있어 매우 중요하다. 따라서 본 논문에서는 여권 영상을 스미어링한 후, 추출된 문자열 중에서 가장 긴 문자열을 선택하고 이 문자열의 좌측과 우측 부분의 두께 중심을 연결하는 직선과 수평선과의 기울기를 이용하여 여권 영상에 대한 각도 보정을 수행한다. 여권 코드 추출은 소벨 연산자와 수평 스미어링, 8방향 윤관선 추적 알고리즘을 적용하여 여권 코드의 문자열 영역을 추출하고, 추출된 여권 코드 문자열 영역에 대해 반복 이진화 방법을 적용하여 코드의 문자열 영역을 이진화 한다, 이진화된 문자열 영역에 대해 여권 코드의 인식율을 높이기 위하여 잡영 가지 제거 알고리즘을 적용하여 개별 문자의 잡영을 제거한 후에 개별 코드를 추출하며, CDM 마스크를 적용하여 추출된 개별코드를 복원한다. 추출된 개별코드는 개선된 퍼지 ART 알고리즘을 제안하여 인식에 적용한다. 실제 여권 영상을 대상으로 실험한 결과, CDM 마스크를 이용하여 추출된 개별 코드를 개선된 퍼지 ART 알고리즘을 적용하여 인식한 방법보다 잡영 제거 알고리즘과 CDM 마스크를 적용하여 개선된 퍼지 ART 알고리즘으로 개별 코드를 인식하는 것이 효율적인 것을 확인하였다. 그리고 기존의 퍼지 ART 알고리즘을 이용하여 개별 코드를 인식하는 경우보다 본 논문에서 제안한 개선된 퍼지 ART 알고리즘을 이용하여 개별 코드를 인식하는 경우가 서로 다른 패턴들이 같은 클러스터로 분류되지 않아 인식 성능이 개선되었다.생산하고 있다. 또한 이러한 자료를 바탕으로 지역통계 수요에 즉각 대처할 수 있다. 더 나아가 이와 같은 통계는 전 국민에 대한 패널자료이기 때문에 통계적 활용의 범위가 방대하다. 특히 개인, 가구, 사업체 등 사회 활동의 주체들이 어떻게 변화하는지를 추적할 수 있는 자료를 생산함으로써 다양한 인과적 통계분석을 할 수 있다. 행정자료를 활용한 인구센서스의 이러한 특징은 국가의 교육정책, 노동정책, 복지정책 등 다양한 정책을 정확한 자료를 근거로 수립할 수 있는 기반을 제공한다(Gaasemyr, 1999). 이와 더불어 행정자료 기반의 인구센서스는 비용이 적게 드는 장점이 있다. 예를 들어 덴마크나 핀란드에서는 조사로 자료를 생산하던 때의 1/20 정도 비용으로 행정자료로 인구센서스의 모든 자료를 생산하고 있다. 특히, 최근 모든 행정자료들이 정보통신기술에 의해 데이터베이스 형태로 바뀌고, 인터넷을 근간으로 한 컴퓨터네트워크가 발달함에 따라 각 부처별로 행정을 위해 축적한 자료를 정보통신기술로 연계${cdot}$통합하면 막대한 조사비용을 들이지 않더라도 인구센서스자료를 적은 비용으로 생산할 수 있는 근간이 마련되었다. 이렇듯 행정자료 기반의 인구센서스가 많은 장점을 가졌지만, 그렇다고 모든 국가가 당장 행정자료로 인구센서스를 대체할 수 있는 것은 아니다. 행정자료로 인구센서스통계를 생산하기 위해서는 각 행정부서별로 사용하는 행정자료들을 연계${cdot}$통합할 수 있도록 국가사회전반에 걸쳐 행정 체제가 갖추어져야 하기 때문이다. 특히 모든 국민 개개인에 관한 기본정보, 개인들이 거주하며 생활하는 단위인 개별 주거단위에 관한 정보가 행정부에 등록되어

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A Study on Analysis of Research Data Repository in Humanities and Social Sciences (re3data를 기반으로 한 인문사회 RDR 연구)

  • Cho, Jane;Park, Jong-Do
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.2
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    • pp.69-87
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    • 2019
  • As the discussions on sharing research data prevail by the chance of the inauguration of the International Open Data Charter, research support organizations in the United States, the United Kingdom, and Japan are encouraging researchers to deposit their findings in a credible repository. Humanities and social sciences field, in which research data sharing culture and storage infrastructure are immature compared to life science and natural science, also needs to establish and operate a reliable storage infrastructure to guarantee the continuous access and utilization of data. This study analyzed the overall operational status of 305 subject repositories registered in re3data for the humanities and social sciences and clustered them according to the operational level using 5 indicators. As a result, 70% of the population were identified as universal clusters, and 20% of the excellent cluster was found to have the largest number of linguistic fields and the German-operated. In addition, this study confirmed through correspondence analysis that there is a relation between the sub-theme fields of humanities and social sciences and the types of data to be archived. The history and art domians are related to images, and social studies are related to statistical data. Linguistics has also been analyzed to be related to audio, plain text, and code.

Study on Brand Experience and Personality Effect on Brand Attitude and Repurchase Intention in Food-Franchised (외식 프랜차이즈 브랜드 경험 및 개성이 브랜드 태도와 재구매의도에 미치는 영향)

  • Yang, Ji-An;Lee, Sang-Yoon;Lee, Dong-Han
    • The Korean Journal of Franchise Management
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    • v.3 no.1
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    • pp.26-45
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    • 2012
  • Market players have realized the importance of brand power and tried to develop effective marketing programs which focus on consumer's brand experience. This study aims to investigate brand experience and brand personality effect on brand attitude which is overall consumer's faith toward brands and repurchase intention in food-franchised by Structural Equation Model. As results, both brand experience and brand personality affect brand attitude although brand experience has more influence than brand personality. As consumers show positive brand experience and attitude, repurchase intention is higher. Brand attitude plays a mediation role in the relation of brand experience and personality, and repurchase intention. Also brand experience shows more influence than others on repurchase intention.

A Design of Authentication Mechanism for Secure Communication in Smart Factory Environments (스마트 팩토리 환경에서 안전한 통신을 위한 인증 메커니즘 설계)

  • Joong-oh Park
    • Journal of Industrial Convergence
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    • v.22 no.4
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    • pp.1-9
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    • 2024
  • Smart factories represent production facilities where cutting-edge information and communication technologies are fused with manufacturing processes, reflecting rapid advancements and changes in the global manufacturing sector. They capitalize on the integration of robotics and automation, the Internet of Things (IoT), and the convergence of artificial intelligence technologies to maximize production efficiency in various manufacturing environments. However, the smart factory environment is prone to security threats and vulnerabilities due to various attack techniques. When security threats occur in smart factories, they can lead to financial losses, damage to corporate reputation, and even human casualties, necessitating an appropriate security response. Therefore, this paper proposes a security authentication mechanism for safe communication in the smart factory environment. The components of the proposed authentication mechanism include smart devices, an internal operation management system, an authentication system, and a cloud storage server. The smart device registration process, authentication procedure, and the detailed design of anomaly detection and update procedures were meticulously developed. And the safety of the proposed authentication mechanism was analyzed, and through performance analysis with existing authentication mechanisms, we confirmed an efficiency improvement of approximately 8%. Additionally, this paper presents directions for future research on lightweight protocols and security strategies for the application of the proposed technology, aiming to enhance security.

Color-related Query Processing for Intelligent E-Commerce Search (지능형 검색엔진을 위한 색상 질의 처리 방안)

  • Hong, Jung A;Koo, Kyo Jung;Cha, Ji Won;Seo, Ah Jeong;Yeo, Un Yeong;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.109-125
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    • 2019
  • As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

Records Management and Archives in Korea : Its Development and Prospects (한국 기록관리행정의 변천과 전망)

  • Nam, Hyo-Chai
    • Journal of Korean Society of Archives and Records Management
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    • v.1 no.1
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    • pp.19-35
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    • 2001
  • After almost one century of discontinuity in the archival tradition of Chosun dynasty, Korea entered the new age of records and archival management by legislating and executing the basic laws (The Records and Archives Management of Public Agencies Ad of 1999). Annals of Chosun dynasty recorded major historical facts of the five hundred years of national affairs. The Annals are major accomplishment in human history and rare in the world. It was possible because the Annals were composed of collected, selected and complied records of primary sources written and compiled by generations of historians, As important public records are needed to be preserved in original forms in modern archives, we had to develop and establish a modern archival system to appraise and select important national records for archival preservation. However, the colonialization of Korea deprived us of the opportunity to do the task, and our fine archival tradition was not succeeded. A centralized archival system began to develop since the establishment of GARS under the Ministry of Government Administration in 1969. GARS built a modem repository in Pusan in 1984 succeeding to the tradition of History Archives of Chosun dynasty. In 1998, GARS moved its headquarter to Taejon Government Complex and acquired state-of-the-art audio visual archives preservation facilities. From 1996, GARS introduced an automated archival management system to remedy the manual registration and management system complementing the preservation microfilming. Digitization of the holdings was the key project to provided the digital images of archives to users. To do this, the GARS purchased new computer/server systems and developed application softwares. Parallel to this direction, GARS drastically renovated its manpower composition toward a high level of professionalization by recruiting more archivists with historical and library science backgrounds. Conservators and computer system operators were also recruited. The new archival laws has been in effect from January 1, 2000. The new laws made following new changes in the field of records and archival administration in Korea. First, the laws regulate the records and archives of all public agencies including the Legislature, the Judiciary, the Administration, the constitutional institutions, Army, Navy, Air Force, and National Intelligence Service. A nation-wide unified records and archives management system became available. Second, public archives and records centers are to be established according to the level of the agency; a central archives at national level, special archives for the National Assembly and the Judiciary, local government archives for metropolitan cities and provinces, records center or special records center for administrative agencies. A records manager will be responsible for the records management of each administrative divisions. Third, the records in the public agencies are registered in the computer system as they are produced. Therefore, the records are traceable and will be searched or retrieved easily through internet or computer network. Fourth, qualified records managers and archivists who are professionally trained in the field of records management and archival science will be assigned mandatorily to guarantee the professional management of records and archives. Fifth, the illegal treatment of public records and archives constitutes a punishable crime. In the future, the public records find archival management will develop along with Korean government's 'Electronic Government Project.' Following changes are in prospect. First, public agencies will digitize paper records, audio-visual records, and publications as well as electronic documents, thus promoting administrative efficiency and productivity. Second, the National Assembly already established its Special Archives. The judiciary and the National Intelligence Service will follow it. More archives will be established at city and provincial levels. Third, the more our society develop into a knowledge-based information society, the more the records management function will become one of the important national government functions. As more universities, academic associations, and civil societies participate in promoting archival awareness and in establishing archival science, and more people realize the importance of the records and archives management up to the level of national public campaign, the records and archival management in Korea will develop significantly distinguishable from present practice.

Accuracy evaluation of treatment plan according to CT scan range in Head and Neck Tomotherapy (두경부 토모테라피 치료 시 CT scan range에 따른 치료계획의 정확성 평가)

  • Kwon, Dong Yeol;Kim, Jin Man;Chae, Moon Ki;Park, Tae Yang;Seo, Sung Gook;Kim, Jong Sik
    • The Journal of Korean Society for Radiation Therapy
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    • v.31 no.2
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    • pp.13-24
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    • 2019
  • Purpose: CT scan range is insufficient for various reasons in head and neck Tomotherapy®. To solve that problem, Re-CT simulation is good because CT scan range affects accurate dose calculations, but there are problems such as increased exposure dose, inconvenience, and a change in treatment schedule. We would like to evaluate the minimum CT scan range required by changing the plan setup parameter of the existing CT scan range. Materials and methods: CT Simulator(Discovery CT590 RT, GE, USA) and In House Head & Neck Phantom are used, CT image was acquired by increasing the image range from 0.25cm to 3.0cm at the end of the target. The target and normal organs were registered in the Head & Neck Phantom and the treatment plan was designed using ACCURAY Precision®. Prescription doses are Daily 2.2Gy, 27 Fxs, Total Dose 59.4Gy. Target is designed to 95%~107% of prescription dose and normal organ dose is designed according to SMC Protocol. Under the same treatment plan conditions, Treatment plans were designed by using five methods(Fixed-1cm, Fixed-2.5cm, Fixed-5cm, Dynamic-2.5cm Dynamic-5cm) and two pitches(0.43, 0.287). The accuracy of dose delivery for each treatment plan was analyzed by using EBT3 film and RIT(Complete Version 6.7, RIT, USA). Results: The accurate treatment plan that satisfying the prescribed dose of Target and the tolerance dose in normal organs(SMC Protocol) require scan range of at least 0.25cm for Fixed-1cm, 0.75cm for Fixed-2.5cm, 1cm for Dynamic-2.5cm, and 1.75cm for Fixed-5cm and Dynamic-5cm. As a result of AnalysisAnalysis by RIT. The accuracy of dose delivery was less than 3% error in the treatment plan that satisfied the SMC Protocol. Conclusion: In case of insufficient CT scan range in head and neck Tomotherapy®, It was possible to make an accurate treatment plan by adjusting the FW among the setup parameter. If the parameter recommended by this author is applied according to CT scan range and is decide whether to re-CT or not, the efficiency of the task and the exposure dose of the patient are reduced.