LOW COMPLEXITY AUTO-EXPOSURE CONTROL FOR COMPUTER VISION AND IMAGING SYSTEMS

    公开(公告)号:US20180048829A1

    公开(公告)日:2018-02-15

    申请号:US15642303

    申请日:2017-07-05

    Inventor: Victor CHAN

    Abstract: Methods, apparatuses, computer-readable medium, and systems are disclosed for performing automatic exposure control (AEC). In one embodiment, a first digital image is captured while applying a first set of values to one or more exposure control parameters. At least one computer vision (CV) operation is performed using image data from the first digital image, thereby generating a first set of CV features from a set of possible CV features. A mask is obtained comprising a value for each feature of the set of possible CV features. Using the mask, a first measure of abundance is obtained of relevant CV features among the first set of CV features extracted from the first digital image. Based on the first measure of abundance of relevant CV features, an updated set of values is generated for applying to the one or more exposure control parameters for capturing a subsequent digital image of the scene.

    CONTRAST-ADAPTIVE NORMALIZED PIXEL DIFFERENCE

    公开(公告)号:US20210125315A1

    公开(公告)日:2021-04-29

    申请号:US16664641

    申请日:2019-10-25

    Inventor: Victor CHAN

    Abstract: Due to complexity constraints, most computer vision (CV) features are not suitable for certain applications such as low-power always-on applications. To address such issues, a contrast-adaptive normalized pixel difference (CA-NPD) is proposed. Unlike conventional NPD techniques, the CA-NPD smooths a metric surface, optimizes contrast discriminability, and enables context sensitive normalization.

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