• Title/Summary/Keyword: Embedded Information Extraction

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Development of Robust-to-Rotation Iris Feature Extraction Algorithms For Embedded System (임베디드 시스템을 위한 회전에 강인한 홍채특징 추출 알고리즘 개발)

  • Kim, Shik
    • The Journal of Information Technology
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    • v.12 no.4
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    • pp.25-32
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    • 2009
  • Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. This paper is appropriate for the embedded environment using local gradient histogram embedded system using iris feature extraction methods have implement. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

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A Fast Iris Feature Extraction Method For Embedded System (Embedded 시스템을 위한 고속의 홍채특징 추출 방법)

  • Choi, Chang-Soo;Min, Man-Gi;Jun, Byoung-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.1
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    • pp.128-134
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    • 2009
  • Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. because High-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system using iris feature extraction methods have implement. Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

Task Extraction from Software Design Models to Improve Energy Efficiency of Embedded Software (임베디드 소프트웨어의 설계모델로부터 에너지 효율을 향상시키기 위한 태스크 도출)

  • Hong, Jang-Eui;Kim, Doo-Hwan
    • The KIPS Transactions:PartD
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    • v.18D no.1
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    • pp.45-56
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    • 2011
  • The importance of low-power embedded system is being increased. The studies on low-power system have been performed in issues of hardware architecture and operating system. However because the behaviors of software control the working of hardware devices, the power analysis of software is one of critical issues in energy-efficient embedded system development. This paper proposes a technique to extract tasks from software design models with considering power consumption. We first define the criteria for task extraction, and then propose the way to separate out the task from UML 2.0 design models. Our technique can provide the chance to reduce the power consumption as well as to fulfill the performance requirement in the early phase of software development.

Grammatical Structure Oriented Automated Approach for Surface Knowledge Extraction from Open Domain Unstructured Text

  • Tissera, Muditha;Weerasinghe, Ruvan
    • Journal of information and communication convergence engineering
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    • v.20 no.2
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    • pp.113-124
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    • 2022
  • News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

Implementation of Embedded System for a Fast Iris Identification Based on USN (고속의 홍채인식을 위한 USN기반의 임베디드 시스템 구현)

  • Kim, Shin-Hong;Kim, Shik
    • IEMEK Journal of Embedded Systems and Applications
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    • v.4 no.4
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    • pp.190-194
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    • 2009
  • Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. Because high-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system with iris feature extraction methods based on USN(Ubiquitous Sensor Network). Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

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Parallelization of Feature Detection and Panorama Image Generation using OpenCL and Embedded GPU (OpenCL 및 Embedded GPU를 이용한 영상 특징 추출 및 파노라마 영상 생성의 병렬화)

  • Kang, Seung Heon;Lee, Seung-Jae;Lee, Man Hee;Park, In Kyu
    • Journal of Broadcast Engineering
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    • v.19 no.3
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    • pp.316-328
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    • 2014
  • In this paper, we parallelize the popular feature detection algorithms, i.e. SIFT and SURF, and its application to fast panoramic image generation on the latest embedded GPU. Parallelized algorithms are implemented using recently developed OpenCL as the embedded GPGPU software platform. We compare the implementation efficiency and speed performance of conventional OpenGL Shading Language and OpenCL. Experimental result shows that implementation on OpenCL has comparable performance with GLSL. Compared with the performance on the embedded CPU in the same application processor, the embedded GPU runs 3~4 times faster. As an example of using feature extraction, panorama image synthesis is performed on embedded GPU by applying image matching using detected features.

An Embedded Information Extraction of Color QR Code for Offline Applications (오프라인 응용을 위한 컬러 QR코드의 삽입 정보 추출 방법)

  • Kim, Jin-soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.9
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    • pp.1123-1131
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    • 2020
  • The quick-response (QR) code is a two-dimensional barcode which is widely being used. Due to several interesting features such as small code size, high error correction capabilities, easy code generation and reading process, the QR codes are used in many applications. Nowadays, a printed color QR code for offline applications is being studied to improve the information storage capacity. By multiplexing color information into the conventional black-white QR code, the storage capacity is increased, however, it is hard to extract the embedded information due to the color crosstalk and geometrical distortion. In this paper, to overcome these problems, a new type of QR code is designed based on the CMYK color model and the local spatial searching as well as the global spatial matching is introduced in the reading process. These results in the recognition rate increase. Through practical experiments, it is shown that the proposed algorithm can perform the bit recognition rate improvement of about 3% to 5%.

A Multi-Strategic Concept-Spotting Approach for Robust Understanding of Spoken Korean

  • Lee, Chang-Ki;Eun, Ji-Hyun;Jeong, Min-Woo;Lee, Gary Geun-Bae;Hwang, Yi-Gyu;Jang, Myung-Gil
    • ETRI Journal
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    • v.29 no.2
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    • pp.179-188
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    • 2007
  • We propose a multi-strategic concept-spotting approach for robust spoken language understanding of conversational Korean in a hostile recognition environment such as in-car navigation and telebanking services. Our concept-spotting method adopts a partial semantic understanding strategy within a given specific domain since the method tries to directly extract predefined meaning representation slot values from spoken language inputs. In spite of partial understanding, we can efficiently acquire the necessary information to compose interesting applications because the meaning representation slots are properly designed for specific domain-oriented understanding tasks. We also propose a multi-strategic method based on this concept-spotting approach such as a voting method. We present experiments conducted to verify the feasibility of these methods using a variety of spoken Korean data.

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Panoramic Image Stitching Using Feature Extracting and Matching on Embedded System

  • Lee, June-Hwan
    • Transactions on Electrical and Electronic Materials
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    • v.18 no.5
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    • pp.273-278
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    • 2017
  • Recently, one of the areas where research is being actively conducted is the Internet of Things (IoT). The field of using the Internet of Things system is increasing, coupled with a remarkable increase of the use of the camera. However, general cameras used in the Internet of Things have limited viewing angles as compared to those available to the human eye. Also, cameras restrict observation of objects and the performance of observation. Therefore, in this paper, we propose a panoramic image stitching method using feature extraction and matching based on an embedded system. After extracting the feature of the image, the speed of image stitching is improved by reducing the amount of computation using the necessary information so that it can be used in the embedded system. Experimental results show that it is possible to improve the speed of feature matching and panoramic image stitching while generating a smooth image.

Recognizing Emotional Content of Emails as a byproduct of Natural Language Processing-based Metadata Extraction (이메일에 포함된 감성정보 관련 메타데이터 추출에 관한 연구)

  • Paik, Woo-Jin
    • Journal of the Korean Society for information Management
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    • v.23 no.2
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    • pp.167-183
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    • 2006
  • This paper describes a metadata extraction technique based on natural language processing (NLP) which extracts personalized information from email communications between financial analysts and their clients. Personalized means connecting users with content in a personally meaningful way to create, grow, and retain online relationships. Personalization often results in the creation of user profiles that store individuals' preferences regarding goods or services offered by various e-commerce merchants. We developed an automatic metadata extraction system designed to process textual data such as emails, discussion group postings, or chat group transcriptions. The focus of this paper is the recognition of emotional contents such as mood and urgency, which are embedded in the business communications, as metadata.