• Journal of the Korea Institute of Building Construction
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• v.16 no.2
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• pp.177-183
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• 2016

The daily report includes the most detailed information and various daily planning and performance data recorded at a site, and includes work types, the number of workers, and the equipment and materials used. However, in the daily reporting process, some information can be omitted or distorted or even made redundant due to there being several steps of manual input. For this reason, the daily report is utilized for a simple report rather than for an appropriate purpose. Thus, to resolve the issues of the existing daily report system mentioned above, a daily report system using a digital pen was developed and then applied to an actual construction site to verify its applicability. As a result, it was found that 96.610% recognition accuracy of handwritten letters could be achieved. In addition, it was no longer necessary to enter the same information multiple times and no additional training or education for using a mobile device was needed. The digital pen-based daily report program developed in this study is expected to contribute to an improvement of information management efficiency and site document management work by addressing the problems of the existing report system.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.175-180
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• 2020

Through case studies for insurance service marketing using artificial intelligence(AI) in the insurtech industry, it investigated how innovative technologies(artificial intelligence, machine learning etc.) are being used in the insurance ecosystems. In particular, through domestic and international case studies, it was examined by Lemonade's service of insurance contracts and getting the indemnity and AI company's service of calculating the compensation through a medical certificate image based on OCR, which brought disruptive innovations using artificial intelligence. As a result of the case analysis, these services have drastically shortened the lead time of insurance contracts and payment through machine learning using numerous customer data based on artificial intelligence. And accurate and reasonable compensation was calculated in the estimation of indemnity, which has a lot of disputes between customers and insurance companies. It was able to increase customer satisfaction and customer value.

• Journal of the Ergonomics Society of Korea
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• v.26 no.2
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• pp.149-155
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• 2007

Recently, various devices requiring text input such as mobile phone IPTV, PDA and UMPC are emerging. The frequency of text entry for them is also increasing. This study was focused on the evaluation of Korean text entry interface. Various models to evaluate text entry interfaces have been proposed. Most of models were based on human cognitive process for text input. The cognitive process was divided into two components; visual scanning process and finger movement process. The time spent for visual scanning process was modeled as Hick-Hyman law, while the time for finger movement was determined as Fitts' law. There are three questions on the model-based evaluation of text entry interface. Firstly, are human cognitive processes (visual scanning and finger movement) during the entry of text sequentially occurring as the models. Secondly, is it possible to predict real text input time by previous models. Thirdly, does the human cognitive process for text input vary according to users' text entry speed. There was time gap between the real measured text input time and predicted time. The time gap was larger in the case of participants with high speed to enter text. The reason was found out investigating Eye-Hand Coordination during text input process. Differently from an assumption that visual scan on the keyboard is followed by a finger movement, the experienced group performed both visual scanning and finger movement simultaneously. Arrival Lead Time was investigated to measure the extent of time overlapping between two processes. 'Arrival Lead Time' is the interval between the eye fixation on the target button and the button click. In addition to the arrival lead time, it was revealed that the experienced group uses the less number of fixations during text entry than the novice group. This result will contribute to the improvement of evaluation model for text entry interface.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.185-196
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• 1999

In this dissertation, a new off-line recognition system is proposed using a subgraph pattern, neural network. After thinning is applied to input characters, balance having a noise elimination function on location is performed. Then as the first step for recognition procedure, circular elements are extracted and recognized. From the subblock HT, space feature points such as endpoint, flex point, bridge point are extracted and a subgraph pattern is formed observing the relations among them. A region where vowel can exist is allocated and a candidate point of the vowel is extracted. Then, using the subgraph pattern dictionary, a vowel is recognized. A same method is applied to extract horizontal vowels and the vowel is recognized through a simple structural analysis. For verification of recognition subgraph in this paper, experiments are done with the most frequently used Myngjo font, Gothic font for printed characters and handwritten characters. In case of Gothic font, character recognition rate was 98.9%. For Myngjo font characters, the recognition rate was 98.2%. For handwritten characters, the recognition rate was 92.5%. The total recognition rate was 94.8% with mixed handwriting and printing characters for multi-font recognition.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1342-1349
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• 1999

본 논문에서는 문서 내의 인접한 두 행 사이에는 일정한 두께의 공백 행이 존재하며 그 공백 행의 기울기는 실제 문서의 기울어진 정도를 반영한다는 사실에 기반하여, 선형적으로 기울어진 문서 영상의 기울기 추정을 위한 고속의 알고리즘을 제안한다. 먼저, 간단한 모폴로지 연산(dilation)을 이용하여 문자행 영역과 공백행 영역을 분리한 후, 이를 일정 간격으로 수직 샘플링하여 수직선 상에 있는 모든 공백행의 중심점(행간점)을 찾는다. 동일한 공백 행 상에 있는 인접한 두 행간점 간에 기울기를 계산하고, 전체 영상으로부터 이들의 분포를 조사하여 최대 빈도를 가지는 기울기를 입력 문서의 기울기로 추정한다. 실험에서는 제안한 알고리즘을 필기체 및 인쇄체를 포함하는 다양한 형태의 가로쓰기 문서에 적용한 결과를 보인다.Abstract In this paper, we propose a fast algorithm to estimate the skew angle of linearly skewed document images. This paper is based on the fact that there is a blank line with uniform thickness between two adjacent text lines and the slope of the line is the same as that of the document. Firstly, we apply a dilation operation to the image to separate blank lines from text lines, and we detect center points of blank lines along the vertically sampled lines. Then we calculate the slope between neighboring center points in the same blank line. Calculated slopes for the entire image are accumulated on the histogram to display the distribution of them. Finally, the peak in the histogram is detected and estimated as the slope of the document image. In the experiments, we adopted a lot of images of various format with hand-printed or machine-printed document to verify our algorithm.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.79-84
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• 2019

Video image based technology is being used in various fields with continuous development. The demand for vision system technology that analyzes and discriminates image objects acquired through cameras is rapidly increasing. Image processing is one of the core technologies of vision systems, and is used for defect inspection in the semiconductor manufacturing field, object recognition inspection such as the number of tire surfaces and symbols. In addition, research into license plate recognition is ongoing, and it is necessary to recognize objects quickly and accurately. In this paper, propose a recognition model through the rotational alignment of objects after checking the angle value of the tilt of the object in the input video image for the recognition of inclined objects such as numbers or symbols marked on the surface. The proposed model can perform object recognition of the rotationally sorted image after extracting the object region and calculating the angle of the object based on the contour algorithm. The proposed model extracts the object region based on the contour algorithm, calculates the angle of the object, and then performs object recognition on the rotationally aligned image. In future research, it is necessary to study template matching through machine learning.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.407-412
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• 2019

In this paper, we propose a technique for processing of speech recognition in korean words. Speech recognition is a technology that converts acoustic signals from sensors such as microphones into words or sentences. Most foreign languages have less difficulty in speech recognition. On the other hand, korean consists of vowels and bottom consonants, so it is inappropriate to use the letters obtained from the voice synthesis system. That improving the conventional structure speech recognition can the correct words recognition. In order to solve this problem, a new algorithm was added to the existing speech recognition structure to increase the speech recognition rate. Perform the preprocessing process of the word and then token the results. After combining the result processed in the Levenshtein distance algorithm and the hashing algorithm, the normalized words is output through the consonant comparison algorithm. The final result word is compared with the standardized table and output if it exists, registered in the table dose not exists. The experimental environment was developed by using a smartphone application. The proposed structure shows that the recognition rate is improved by 2% in standard language and 7% in dialect.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.105-110
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• 2021

In this paper, we design and implement an Android mobile application that helps hearing impaired people communicate based on STT(Speech-to-Text) and TTS(Text-to-Speech) APIs and accelerometer sensor of a smartphone. This application provides the ability to record what the hearing-Impairment person's interlocutor is saying with a microphone, convert it to text using the STT API, and display it to the hearing-Impairment person. In addition. In addition, when a hearing-impaired person inputs a text using the TTS API, it is converted into voice and told to the interlocutor. When a hearing-impaired person shakes their smartphone, an accelerometer based background service function is provided to run the application. The application implemented in this paper provides a function that allows hearing impaired people to communicate easily with other people when communicating with others without using sign language as a video call.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.47-52
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• 2018

Named Entity Recognition is a system that extracts entity names such as Persons(PS), Locations(LC), and Organizations(OG) that can have a unique meaning from a document and determines the categories of extracted entity names. Recently, Bi-LSTM-CRF, which is a combination of CRF using the transition probability between output data from LSTM-based Bi-LSTM model considering forward and backward directions of input data, showed excellent performance in the study of object name recognition using deep-learning, and it has a good performance on the efficient embedding vector creation by character and word unit and the model using CNN and LSTM. In this research, we describe the Bi-LSTM-CNN-CRF model that enhances the features of the Korean named entity recognition system and propose a method for constructing the traditional culture corpus. We also present the results of learning the constructed corpus with the feature augmentation model for the recognition of Korean object names.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.345-353
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• 2019

Several studies have been proposed to improve storage space efficiency by expressing binary trie data structure as a linear binary bit string. Compact binary tree approach generated using one binary trie increases the key search time significantly as the binary bit string becomes very long as the size of the input key set increases. In order to reduce the key search range, a hierarchical compact binary tree technique that hierarchically expresses several small binary compact trees has been proposed. The search time increases proportionally with the number and length of binary bit streams. In this paper, we generate several binary compact trees represented by full binary tries hierarchically. The search performance is improved by allowing a path for the binary bit string corresponding to the search range to be determined through simple numeric conversion. Through the performance evaluation using the worst time and space complexity calculation, the proposed method showed the highest performance for retrieval and key insertion or deletion. In terms of space usage, the proposed method requires about 67% ~ 68% of space compared to the existing methods, showing the best space efficiency.