映像情報メディア学会誌
Online ISSN : 1881-6908
Print ISSN : 1342-6907
ISSN-L : 1342-6907
64 巻, 3 号
選択された号の論文の30件中1~30を表示しています
ふぉーかす
小特集
イメージセンサ技術の最新動向
1. 2009 IISWレビュー
2. 周囲光電荷消去型3Dイメージセンサ
3. HARP撮像デバイスの開発状況とその応用
技術解説
講  座
マルチメディア検索の最先端(第3回)
知っておきたいキーワード(第50回)
私の研究開発ツール(第32回)
大学発のベンチャービジネス
100行で書く画像処理最先端(第3回)
ニュース
論文・研究速報
論文特集 イメージセンシング技術とその応用
特集論文
特集研究速報
  • 秋田 純一, 前田 唯
    2010 年 64 巻 3 号 p. 413-415
    発行日: 2010/03/01
    公開日: 2010/06/01
    ジャーナル フリー
    Pixels in conventional imaging systems are located in lattice sites, and this lattice placement of pixels causes jaggy artifacts in the image, especially at the edges of slanted lines with high-intensity contrast, which often results in severe defects in the image quality. The conventional approaches to overcoming this problem of jaggedness are to increase the number of pixels and to use anti-aliasing. However, the number of pixels is limited by the physical pixel size and the quantity of image information, while anti-aliasing intrinsically causes blurred images. The authors have been researching and evaluating image systems with pseudorandom pixel placement to reduce the effects of jaggy artifacts. We describe here the design of an image sensor that contains pixels with both pseudorandom and convectional lattice placement using an identical active pixel sensor (APS) pixel circuit. We also describe the preliminary experimental results obtained by testing the fabricated image sensors.
  • 木村 孝之, 横山 裕大郎, 増澤 徹
    2010 年 64 巻 3 号 p. 416-418
    発行日: 2010/03/01
    公開日: 2010/06/01
    ジャーナル フリー
    To improve the frame rate of a two-dimensional integrated magnetic sensor, the pixel structure and readout circuits were re-examined. The frame rate was improved by reducing the noise of the horizontal shift register by lowering the drive frequency and parallel reading (with 16 channels). With this idea, two-dimensional integrated magnetic sensors were designed and fabricated with the standard 0.35 μm CMOS process on silicon. The type of Hall sensor is n-type Hall sensor that uses an inversion layer under the gate oxide of the MOSFET. The Hall sensors were arrayed (64×64), and the control digital circuits and output amplifier were also integrated into the same chip. “One pixel” was 50×50 μm, and the entire chip was 4.9×4.9 mm. The frame rate was 7813 frames/sec at a 2-MHz horizontal shift register frequency. The average sensitivity of these sensors was 72.9 mV/(mA·T). The two-dimensional magnetic flux distribution was measured with a 3000-rpm, 1-mm-diameter Nd-Fe-B rare-earth permanent rotating magnet without image lag. From the measurement results, a high frame-rate magnetic sensor for motor control was successfully fabicated.
  • 金 允ギョン, 池田 誠, 浅田 邦博
    2010 年 64 巻 3 号 p. 419-422
    発行日: 2010/03/01
    公開日: 2010/06/01
    ジャーナル フリー
    With the downscaling of CMOS technology, interconnect layers are multi-stratified since the number of metal levels has increased. However, this multi-metal-layer structure above the photodiodes affects sensitivity, which is important for obtaining optimal performance from CMOS image sensors. This paper analyzes the light-transmission characteristics on multi-metal layers (interconncet layers). To evaluate what effect standard CMOS-process technologies have on multi-metal layers, we developed a method of calculating the transmitted light intensity through the multi-metal layers. We found the transmitted light intensity from the calculated results using the transfer matrix method for standard CMOSs ranging in size from 1.2 μm to 22 nm.
論文
  • Yongqing Sun, Satoshi Shimada, Masashi Morimoto, Yukinobu Taniguchi
    2010 年 64 巻 3 号 p. 423-434
    発行日: 2010/03/01
    公開日: 2010/06/01
    ジャーナル フリー
    In this paper we present a novel approach to modeling visual concepts effectively and automatically using web images. The selection of training data (positive and negative samples) is strongly related to the quality of learning algorithms and is an especially crucial step when using noisy web images. In this scheme, first, images are represented by regions from which training samples are selected. Second, region features effectively representing a semantic concept are determined, and on their basis, the representative regions corresponding to the concept are selected as reliable positive samples. Third, high quality negative samples are determined using the selected positive samples. Last, the visual model associated with a semantic concept is built through an unsupervised learning process. The presented scheme is completely automatic and performs well for generic images because of its robustness in learning from diverse web images. Experimental results demonstrate its effectiveness.
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