Recognition of Defocused Patterns

• Item type: Trans(1)
• 公開日: 2014-07-25
• タイトル: Recognition of Defocused Patterns
• タイトル / 言語: en
• タイトル: Recognition of Defocused Patterns
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [Resarch Paper - Express Paper] pattern recognition, coded aperture, defocus, local feature
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Osaka Prefecture University
• 著者所属: Osaka Prefecture University
• 著者所属: Hiroshima City University
• 著者所属: Osaka Prefecture University
• 著者所属(英): en
• 著者所属(英): Osaka Prefecture University
• 著者所属(英): en
• 著者所属(英): Osaka Prefecture University
• 著者所属(英): en
• 著者所属(英): Hiroshima City University
• 著者所属(英): en
• 著者所属(英): Osaka Prefecture University
• 著者名: Masakazu, Iwamura; Masashi, Imura; Shinsaku, Hiura; Koichi, Kise
• 著者名(英): Masakazu, Iwamura; Masashi, Imura; Shinsaku, Hiura; Koichi, Kise
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: The paper addresses the recognition problem of defocused patterns. Though recognition algorithms assume that the input images are focused and sharp, it does not always hold on actual camera-captured images. Thus, a recognition method that can recognize defocused patterns is required. In this paper, we propose a novel recognition framework for defocused patterns, relying on a single camera without a depth sensor. The framework is based on the coded aperture which can recover a less-degraded image from a defocused image if depth is available. However, in the problem setting of “a single camera without a depth sensor,” estimating depth is ill-posed and an assumption is required to estimate the depth. To solve the problem, we introduce a new assumption suitable for pattern recognition; templates are known. It is based on the fact that in pattern recognition, all templates must be available in advance for training. The experiments confirmed that the proposed method is fast and robust to defocus and scaling, especially for heavily defocused patterns.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: The paper addresses the recognition problem of defocused patterns. Though recognition algorithms assume that the input images are focused and sharp, it does not always hold on actual camera-captured images. Thus, a recognition method that can recognize defocused patterns is required. In this paper, we propose a novel recognition framework for defocused patterns, relying on a single camera without a depth sensor. The framework is based on the coded aperture which can recover a less-degraded image from a defocused image if depth is available. However, in the problem setting of “a single camera without a depth sensor,” estimating depth is ill-posed and an assumption is required to estimate the depth. To solve the problem, we introduce a new assumption suitable for pattern recognition; templates are known. It is based on the fact that in pattern recognition, all templates must be available in advance for training. The experiments confirmed that the proposed method is fast and robust to defocus and scaling, especially for heavily defocused patterns.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12628065
• 書誌情報: IPSJ Transactions on Computer Vision and Applications （CVA）; 巻 6, p. 48-52, 発行日 2014-07-25
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-6695
• 出版者 / 言語: ja
• 出版者: 情報処理学会