Jungwha Kim

A comparison of binarization methods for historical archive documents

This paper compares several alternative binarization algorithms for historical archive documents, by evaluating their effect on end-to-end word recognition performance in a complete archive document recognition system utilising a commercial OCR engine. The algorithms evaluated are: global thresholding; Niblacks and Sauvolas algorithms; adaptive versions of Niblacks and Sauvolas algorithms; and Niblacks and Sauvolas algorithms applied to background removed images. We found that, for our archive documents, Niblacks algorithm can achieve better performance than Sauvolas (which has been claimed as an evolution of Niblacks algorithm), and that it also achieved better performance than the internal binarization provided as part of the commercial OCR engine.

High accuracy handwritten Chinese character recognition by improved feature matching method

Proposes some strategies to improve the recognition performance of a feature matching method for handwritten Chinese character recognition (HCCR). Favorable modifications are given to all stages throughout the recognition. In pre-processing, we devised a modified nonlinear normalization algorithm and a connectivity-preserving smoothing algorithm. For feature extraction, an efficient directional decomposition algorithm and a systematic approach to design a blurring mask are presented. Finally, a modified LVQ3 algorithm is applied to optimize the reference vectors for classification. The integrated effect of these strategies significantly improves the recognition performance. Recognition results on the large-vocabulary databases ETL8B2 and ETL9B are promising.

Recognition of logic diagrams by identifying loops and rectilinear polylines

Proposed is a system that recognizes logic symbols and their interconnections on logic diagrams. The input diagram, digitized by scanner, is converted into a set of line segments through a sequence of picture processing operations. Then symbols and connections are extracted by identifying loops and rectilinear polylines utilizing a model-base in which symbols are graphically described. Experiment with a number of logic diagrams shows that the system correctly recognizes more than 96% of logic symbols and connections on an A4-size diagram with an average complexity within 15 s on a workstation.<<ETX>>

Metadata schema for context-aware augmented reality applications in cultural heritage domain

As cultural heritage domain enters the digital heritage era based on advanced digital technology, Augmented Reality(AR) technology has arisen as a new medium for enhancing user experience by augmenting additional information or content. Although there have been several AR applications in the cultural heritage domain, insufficient re-usability and interoperability of AR applications has inhibited the development of AR ecosystems. To address these issues, we propose the 5W1H-based metadata schema for context-aware AR applications in the cultural heritage domain, which consists of the PoI-AR Anchor-AR Contents relation based on Who, When, Where, What, Why, How and its whole metadata structure. We also propose a modified AR reference model to investigate the usefulness and effectiveness of the proposed schema. The 5W1H-based metadata schema provides a context-aware mediating platform that secures extensibility for further contextual information, and its whole metadata structure ensures the re-usability of the AR contents and interoperability of AR applications. The modified AR reference model describes the universal workflow and the generic framework for AR applications to encourage compatibility of following AR applications. Through these proposals, contextualized content retrieval according to user preference will be possible for AR applications in the cultural heritage domain.

AMARA: the affective museum of art resource agent

This interactive system uses an embedded agent for question-based art collection search on the platform of the Indianapolis Museum of Art website. Unlike a keyword search box, AMARA helps users browse and search for artwork by asking them simple questions with answers mapped to social tags. Thus, the users do not need to be subject matter experts to input specific terms to search. In designing AMARA, we focused on creating an enjoyable browsing experience and helping users to determine their known and unknown art preferences.

AR Reference Model for K-Culture Time Machine

In this paper, we introduce the K-Culture Time Machine Project, which develops a mobile AR platform for visualizing time-space connected cultural contents of Korea. Existing AR Applications in cultural heritage domains are currently not interoperable and cannot reuse content. To solve this problem, we developed the modified AR reference model as generic framework of a context-aware AR platform; and we developed the context-aware AR platform with several core technologies according to this model. For back-end, we established the Korean Cultural Heritage Data Model (KCHDM) to aggregate the heterogeneous cultural heritage databases in Korea. We also developed the semi-auto time-space correlation generation module for domain experts. Moreover, we developed the authoring tool to generate the time-space connected AR contents. For the front-end, we developed the vision- and sensor-based spatial data composition technology to perform the solid tracking in outdoor environment and context-aware AR framework. Through the UI/UX and 3D contents, whole technologies are packaged into the mobile AR platform. As a validation process for the application, a mobile AR application for the Korean world cultural heritage was developed. Based on this project, an interoperable AR platform that responds with heterogeneous database would be developed and smart tour guide of the cultural heritage site would be possible.

A linearization technique for linearly inseparable patterns

This paper concerns a technique which transforms a set of linearly inseparable binary patterns to a set of linearly separable one. Using the technique, a framework to train multilayer perceptrons without iteration is introduced. The trained multilayer perceptrons using these ideas use only hard limiters as neutrons and integer weights and thresholds. Hence accurate hardware implementation of the networks can be realized using the readily available VLSI technology.<<ETX>>

An Ontology-Based Augmented Reality Application Exploring Contextual Data of Cultural Heritage Sites

In this study, we present a novel Augmented Reality (AR) application for providing contextual information of cultural heritage sites. Whereas most location-based AR systems are designed to show simple information on a Point of Interest (POI) in the real world, the suggested application offers information related to various cultural heritages including tangible and intangible heritages linked to the POI. is is accomplished by a cultural heritage ontology that aggregates heterogeneous data and reorganizes information in themes and relationships. The users can browse information such as the person who created the POI and events that took place at the location as separate entities. We implemented the application for Injeongjeon and the vicinity of Changdeokgung palace and conducted user studies to determine how people explore and consume contextual information at the heritage site. We provide directions that will be useful for designing information to support heritage site visiting, and discuss how the AR technology could improve the application.

Ontology-based mobile augmented reality in cultural heritage sites: information modeling and user study

Augmented reality (AR) has received much attention in the cultural heritage domain as an interactive medium for requesting and accessing information regarding heritage sites. In this study, we developed a mobile AR system based on Semantic Web technology to provide contextual information about cultural heritage sites. Most location-based AR systems are designed to present simple information about a point of interest (POI), but the proposed system offers information related to various aspects of cultural heritage, both tangible and intangible, linked to the POI. This is achieved via an information modeling framework where a cultural heritage ontology is used to aggregate heterogeneous data and semantically connect them with each other. We extracted cultural heritage data from five web databases and modeled contextual information for a target heritage site (Injeongjeon Hall and its vicinity in Changdeokgung Palace in South Korea) using the selected ontology. We then implemented a mobile AR application and conducted a user study to assess the learning and engagement impacts of the proposed system. We found that the application provides an agreeable user experience in terms of its affective, cognitive, and operative features. The results of our analysis showed that specific usage patterns were significant with regard to learning outcomes. Finally, we explored how the study’s key findings can provide practical design guidance for system designers to enhance mobile AR information systems for heritage sites, and to show system designers how to support particular usage patterns in order to accommodate specific user experiences better.

A Multiprocessor System For Real-time Implementation Of Spatial Domain Digital Filters

This paper presents an efficient multiprocessor system for real-time implementation of spatial domain digital filters. This multiprocessor system uses a specially designed digital signal processor (DSP) as a node and operates asynchronously without requirement for global synchronization between DSPs. It is based upon an efficient algorithm decomposition technique which minimizes data communication requirements between DSPs without increasing computational complexity. A very high order spatial domain digital filter can be implemented by cascading lower order sections with the total number of the processors increasing only at a linear rate. This multipro- cessor system is an implementation of a wavefront array processor for spatial domain filters.