Implementation of PDF417 Two-Dimensional Barcode Decoder
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| Title: | Implementation of PDF417 Two-Dimensional Barcode Decoder |
|---|---|
| Authors: | Hahn, Hee Il, Joung, Joung Goo |
| Publisher Information: | The Institute of Electronics Engineers of Korea |
| Publication Year: | 2008 |
| Collection: | CLICK (Cooperative Link Center in KOREA) |
| Time: | 621 |
| Description: | In this paper we present a barcode reader to decode two-dimensional symbology PDF417 and propose a novel method to extract the bar-space Patterns directly from the gray-level barcode image, which employs the location and the distance between extreme points of each row or column of the barcode image. This algerian proves to be very robust from the high convolutional distortion environments such as defocussing and warping, even under badly illuminating condition. If the scanned barcode image is a result of the convolution of a Gaussian-shaped point spread function with a hi-level image, popular image segmentation methods such as image thresholding can not distinguish between very narrow bar-space patterns. The Proposed algorithm shows improved Performance over current barcode readers. 본 논문에서는 가장 널리 사용되는 이차원 바코드 체계인 PDF417 에 대하여 디지털 카메라를 통하여 입력한 영상으로부터 시작심볼 또는 종료심볼을 검색함으로써 이차원 바코드 영역을 찾아낸 다음, 그 영역으로부터 코드워드를 추출하여 디코드하는 알고리즘을 설계하여 실시간으로 구현하였다. 코드워드를 추출하는데 있어서, 바코드 영상을 이진화하지 않고 영상을 스캔하면서 각 행의 프로파일에서 극점의 위치와 상대적인 거리등을 분석함으로써 바-스페이스 패턴을 추출하는 알고리즘을 제안하였다. 제안한 알고리즘은 비 균일한 조명환경 하에서도 초점이 제대로 맞지 않거나 다양한 컨볼류션 왜곡이 있더라도 매우 강인한 특성을 보여 줄 뿐만 아니라 처리속도가 매우 빠르므로 실시간으로 구현할 수 있는 장점이 있다. |
| Document Type: | other/unknown material |
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| Language: | English |
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| Accession Number: | edsbas.62FEAD11 |
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| Items | – Name: Title Label: Title Group: Ti Data: Implementation of PDF417 Two-Dimensional Barcode Decoder – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hahn%2C+Hee+Il%22">Hahn, Hee Il</searchLink><br /><searchLink fieldCode="AR" term="%22Joung%2C+Joung+Goo%22">Joung, Joung Goo</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: The Institute of Electronics Engineers of Korea – Name: DatePubCY Label: Publication Year Group: Date Data: 2008 – Name: Subset Label: Collection Group: HoldingsInfo Data: CLICK (Cooperative Link Center in KOREA) – Name: Subject Label: Time Group: Su Data: 621 – Name: Abstract Label: Description Group: Ab Data: In this paper we present a barcode reader to decode two-dimensional symbology PDF417 and propose a novel method to extract the bar-space Patterns directly from the gray-level barcode image, which employs the location and the distance between extreme points of each row or column of the barcode image. This algerian proves to be very robust from the high convolutional distortion environments such as defocussing and warping, even under badly illuminating condition. If the scanned barcode image is a result of the convolution of a Gaussian-shaped point spread function with a hi-level image, popular image segmentation methods such as image thresholding can not distinguish between very narrow bar-space patterns. The Proposed algorithm shows improved Performance over current barcode readers. 본 논문에서는 가장 널리 사용되는 이차원 바코드 체계인 PDF417 에 대하여 디지털 카메라를 통하여 입력한 영상으로부터 시작심볼 또는 종료심볼을 검색함으로써 이차원 바코드 영역을 찾아낸 다음, 그 영역으로부터 코드워드를 추출하여 디코드하는 알고리즘을 설계하여 실시간으로 구현하였다. 코드워드를 추출하는데 있어서, 바코드 영상을 이진화하지 않고 영상을 스캔하면서 각 행의 프로파일에서 극점의 위치와 상대적인 거리등을 분석함으로써 바-스페이스 패턴을 추출하는 알고리즘을 제안하였다. 제안한 알고리즘은 비 균일한 조명환경 하에서도 초점이 제대로 맞지 않거나 다양한 컨볼류션 왜곡이 있더라도 매우 강인한 특성을 보여 줄 뿐만 아니라 처리속도가 매우 빠르므로 실시간으로 구현할 수 있는 장점이 있다. – Name: TypeDocument Label: Document Type Group: TypDoc Data: other/unknown material – Name: Format Label: File Description Group: SrcInfo Data: pdf – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: http://click.ndsl.kr/servlet/LinkingFullTextView?service_code=04&dbt=JAKO&cn=JAKO200402612627363 – Name: URL Label: Availability Group: URL Data: http://click.ndsl.kr/servlet/LinkingFullTextView?service_code=04&dbt=JAKO&cn=JAKO200402612627363 – Name: AN Label: Accession Number Group: ID Data: edsbas.62FEAD11 |
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