• ETRI Journal
• /
• v.33 no.1
• /
• pp.78-88
• /
• 2011

In this paper, we present the Touch Text exTractor (Touch TT), an interactive text segmentation tool for the extraction of scene text from camera-based images. Touch TT provides a natural interface for a user to simply indicate the location of text regions with a simple touchline. Touch TT then automatically estimates the text color and roughly locates the text regions. By inferring text characteristics from the estimated text color and text region, Touch TT can extract text components. Touch TT can also handle partially drawn lines which cover only a small section of text area. The proposed system achieves reasonable accuracy for text extraction from moderately difficult examples from the ICDAR 2003 database and our own database.

• Journal of Korean Elementary Science Education
• /
• v.29 no.4
• /
• pp.526-537
• /
• 2010

The purpose of this study was to compare the effects of two different types of texts, which were narrative and expository, on the understanding of content. Elementary students' perceptions of the two types of the texts were also investigated. In the comparison of the effects on the understanding of the text contents, test scores of mind-mapping, closed-answer question, and essay test were used. The analyses of mind-mapping tests showed narrative text was more effective to figure out main concepts of the text throughout the mind-mapping test. But expository text was more effective in the hierarchical organization of the concepts. In the closed-answer questions and essay test, narrative text was more effective than expository text. However when the contents of text were difficult and complex, there was no meaningful difference between the two types of texts. The analyses of students' perceptions of the texts showed that narrative texts were preferred. Students perceived that the narrative text was more interesting and familiar. However, the perceptions of helpful text for their science learning were not different by the types of texts.

• Journal of The Korean Association For Science Education
• /
• v.30 no.1
• /
• pp.27-41
• /
• 2010

Scientific texts are some of major sources for scientific understanding. Therefore, reading scientific texts should be considered as an important learning activity. However, there is little research about reading scientific text in Korea. In this study, as a starting point for research about reading scientific text, lists of scientific text constituents and scientific text functions are suggested based on a comprehensive literature review. The study also reviewed how scientific text structure, familarity of scientific text and analogy involved in scientific text can affect students' scientific understanding through reading scientific text. Finally, further study plans, such as analysis of actual science textbooks using the lists suggested in this study as well as the investigation of actual students' thinking processes when reading scientific text, were described.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4072-4091
• /
• 2015

A separation of text and non-text elements plays an important role in document layout analysis. A number of approaches have been proposed but the quality of separation result is still limited due to the complex of the document layout. In this paper, we present an efficient method for the classification of text and non-text components in document image. It is the combination of whitespace analysis with multi-layer homogeneous regions which called recursive filter. Firstly, the input binary document is analyzed by connected components analysis and whitespace extraction. Secondly, a heuristic filter is applied to identify non-text components. After that, using statistical method, we implement the recursive filter on multi-layer homogeneous regions to identify all text and non-text elements of the binary image. Finally, all regions will be reshaped and remove noise to get the text document and non-text document. Experimental results on the ICDAR2009 page segmentation competition dataset and other datasets prove the effectiveness and superiority of proposed method.

• International Journal of Knowledge Content Development & Technology
• /
• v.2 no.2
• /
• pp.5-16
• /
• 2012

Today, most researchers conduct their studies through the full-text of e-journals. Therefore, an important base for domestic development of science and technology is to obtain the full-text of quality e-journals by overseas researchers and to provide it to Korea's researchers. This study aims to build a system based on the National Archiving Center for the full-text of e-journals and to make a service system for providing them to the public by acquiring the full-text of quality overseas e-journals. To do this, an analysis was made of the outcome of introducing such a system for full-text of e-journals in comparison with the investment. As a result, 112 more institutions, that is, from 47 institutions to 159 institutions, have introduced the system as of 2012, and the number of downloaded full-texts increased at least 2.17 times.

• Journal of Information Science Theory and Practice
• /
• v.9 no.4
• /
• pp.15-34
• /
• 2021

Text clustering is one of the most commonly used methods for detecting themes or types of documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to be used for the understanding of Arabic text, especially with respect to terms extraction, unsupervised feature selection, and clustering algorithms. In most cases, terms extraction focuses on nouns. Clustering simplifies the understanding of an Arabic text like the text of the Quran; it is important not only for Muslims but for all people who want to know more about Islam. This paper discusses the complexity and limitations of Arabic text clustering in the Quran based on their themes. Unsupervised feature selection does not consider the relationships between the selected features. One weakness of clustering algorithms is that the selection of the optimal initial centroid still depends on chances and manual settings. Consequently, this paper reviews literature about the three major stages of Arabic clustering: terms extraction, unsupervised feature selection, and clustering. Six experiments were conducted to demonstrate previously un-discussed problems related to the metrics used for feature selection and clustering. Suggestions to improve clustering of the Quran based on themes are presented and discussed.

• International Journal of Computer Science & Network Security
• /
• v.22 no.7
• /
• pp.220-228
• /
• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• Journal of Korean Elementary Science Education
• /
• v.30 no.2
• /
• pp.232-241
• /
• 2011

The purpose of this study was to compare socio-linguistic characteristics and instructional influences of two different types of texts, which were narrative and expository. Socio-linguistic characteristics of two different types of texts were analyzed in their content specialization, linguistic formality, and social-pedagogic relationships. Expository texts showed strong scientific classification, and medium level of linguistic formality, and low level of social-pedagogic relationships. Narrative texts showed different characteristics. The instructional effects were investigated with 91 fifth grade elementary students in three classes. Each class was randomly assigned into three groups: expository text group, narrative text group, control group. The results showed that the science achievement scores of the narrative text group was higher than those of other groups. The affective domain test scores of the expository text group were higher than other groups. The perception of students on informational science text were generally positive both types of texts.

• Journal of Information Science Theory and Practice
• /
• v.10 no.spc
• /
• pp.86-95
• /
• 2022

Online recruitment websites discuss job demands in various fields, and job postings contain detailed job specifications. Analyzing this text can elucidate the features that determine job salaries. Text embedding models can learn the contextual information in a text, and explainable artificial intelligence frameworks can be used to examine in detail how text features contribute to the models' outputs. We collected 733,625 job postings using the WORKNET API and classified them into low, mid, and high-range salary groups. A text embedding model that predicts job salaries based on the text in job postings was trained with the collected data. Then, we applied the SHapley Additive exPlanations (SHAP) framework to the trained model and discovered the significant words that determine each salary class. Several limitations and remaining words are also discussed.

• English Language & Literature Teaching
• /
• v.17 no.3
• /
• pp.161-175
• /
• 2011

This paper examines Korean EFL high school students' reader responses on an expository text and a narrative text with the same topic. The purpose of the study is to investigate whether they have different reading models depending on the two genres and whether there are any differences depending on the learners' proficiency levels. The analysis focuses on textual, critical, and aesthetic reading models in the reader responses written in English by science-gifted high school students (N=30). The results show that the participants have different reading models in reading an expository text and a narrative text. They tend to read the expository text in a more critical way while reading the narrative text in a more personal and emotional way. Moreover, regardless of the proficiency levels, they wrote longer responses on the narrative text than the expository text. However, the proficiency level of English does not support any significant differences in the types of reading models. The findings provide Korean EFL high school students' characteristics in L2 reading and suggest the pedagogical implication to pursue linguistic development as well as reading for pleasure.