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    • 1. 发明申请
    • SYSTEM AND METHOD FOR NON-COOPERATIVE IRIS IMAGE ACQUISITION
    • 用于非合作性IRIS图像获取的系统和方法
    • US20110150334A1
    • 2011-06-23
    • US13055250
    • 2009-07-22
    • Eliza Yingzi DuZhi ZhouEmrah Arslanturk
    • Eliza Yingzi DuZhi ZhouEmrah Arslanturk
    • G06K9/34
    • G06K9/00604
    • A method segments iris images from eye image data captured from non-cooperative subjects. The method includes receiving a frame of eye image data, and determining whether a pupil exists in the image by detecting glare areas in the image. Upon finding a pupil, subsequent images are processed with reference to the pupil location and a radius is calculated for the pupil. A k means clustering method and principal component analysis are used to locate pupil boundary points, which are fitted to a conic. Using the pupil boundary, an angular derivative is computed for each frame having a pupil and iris boundary points are fitted to a conic to identify an iris region between the iris boundary and the pupil boundary. Noise data are then removed from the iris region to generate an iris segment. A method for evaluating iris frame quality and iris image segmentation quality is also disclosed.
    • 一种方法从非合作对象捕获的眼图数据中分割虹膜图像。 该方法包括接收一帧眼图数据,并通过检测图像中的眩光区域来确定图像中是否存在瞳孔。 在找到瞳孔时,参考瞳孔位置处理随后的图像,并计算瞳孔的半径。 A k表示聚类方法,主成分分析用于定位适合于锥体的瞳孔边界点。 使用瞳孔边界,对于具有瞳孔的每个帧计算角度导数,并且将虹膜边界点拟合到圆锥,以识别虹膜边界和瞳孔边界之间的虹膜区域。 然后从虹膜区域移除噪声数据,以产生虹膜段。 还公开了一种用于评估虹膜框架质量和虹膜图像分割质量的方法。
    • 2. 发明授权
    • System and method for non-cooperative iris image acquisition
    • 非合作虹膜图像采集系统和方法
    • US08644565B2
    • 2014-02-04
    • US13055250
    • 2009-07-22
    • Eliza Yingzi DuZhi ZhouEmrah Arslanturk
    • Eliza Yingzi DuZhi ZhouEmrah Arslanturk
    • G06K9/00
    • G06K9/00604
    • A method segments iris images from eye image data captured from non-cooperative subjects. The method includes receiving a frame of eye image data, and determining whether a pupil exists in the image by detecting glare areas in the image. Upon finding a pupil, subsequent images are processed with reference to the pupil location and a radius is calculated for the pupil. A k means clustering method and principal component analysis are used to locate pupil boundary points, which are fitted to a conic. Using the pupil boundary, an angular derivative is computed for each frame having a pupil and iris boundary points are fitted to a conic to identify an iris region between the iris boundary and the pupil boundary. Noise data are then removed from the iris region to generate an iris segment. A method for evaluating iris frame quality and iris image segmentation quality is also disclosed.
    • 一种方法从非合作对象捕获的眼图数据中分割虹膜图像。 该方法包括接收一帧眼图数据,并通过检测图像中的眩光区域来确定图像中是否存在瞳孔。 在找到瞳孔时,参考瞳孔位置处理随后的图像,并计算瞳孔的半径。 A k表示聚类方法,主成分分析用于定位适合于锥体的瞳孔边界点。 使用瞳孔边界,对于具有瞳孔的每个帧计算角度导数,并且将虹膜边界点拟合到圆锥,以识别虹膜边界和瞳孔边界之间的虹膜区域。 然后从虹膜区域移除噪声数据,以产生虹膜段。 还公开了一种用于评估虹膜框架质量和虹膜图像分割质量的方法。
    • 5. 发明授权
    • High dynamic range data format conversions for digital media
    • 数字媒体的高动态范围数据格式转换
    • US08880571B2
    • 2014-11-04
    • US11418627
    • 2006-05-05
    • Sridhar SrinivasanZhi Zhou
    • Sridhar SrinivasanZhi Zhou
    • G06F7/00G06F15/00H04N1/60H03M7/24H04N1/407
    • H03M7/24H04N1/407H04N1/6027
    • One or more continuous mappings are defined at a digital media encoder to convert input digital media data in a first high dynamic range format to a second format with a smaller dynamic range than the first format. The encoder converts the input digital media data to the second format with the smaller dynamic range using the continuous mapping and one or more conversion parameters relating to the continuous mapping. The encoder encodes the converted digital media data in a bitstream along with the conversion parameter(s). The conversion parameter(s) enable a digital media decoder to convert the converted digital media data back to the first high dynamic range format from the second format with the smaller dynamic range. Techniques for converting different input formats with different dynamic ranges are described.
    • 在数字媒体编码器处定义一个或多个连续映射,以将第一高动态范围格式的输入数字媒体数据转换成具有比第一格式更小的动态范围的第二格式。 编码器使用连续映射和与连续映射相关的一个或多个转换参数将输入数字媒体数据转换为具有较小动态范围的第二格式。 编码器将转换的数字媒体数据与转换参数一起编码在比特流中。 转换参数使得数字媒体解码器能够将转换的数字媒体数据从具有较小动态范围的第二格式转换回第一高动态范围格式。 描述用于转换具有不同动态范围的不同输入格式的技术。
    • 8. 发明授权
    • Small detail reservation in content-adaptive quantization
    • 内容自适应量化中的小细节预留
    • US08295346B2
    • 2012-10-23
    • US12420763
    • 2009-04-08
    • Zhi ZhouYeongtaeg Kim
    • Zhi ZhouYeongtaeg Kim
    • H04N7/12H04N11/02H04N11/04G06K9/36G06K9/00H03M7/00
    • H04N19/186H04N19/124H04N19/14H04N19/176H04N19/61
    • Video processing systems and methods for preservation of small details in video undergoing quantization is discussed. Small details are preserved by identifying an area of interest within a video frame, determining whether small details are present within the selected portion of the video frame, and further determining whether those small details may be lost during quantization. In the event that small details are present in the selected portion of the video frame and may be lost during quantization, a color-shifting operation may be performed on one or more color components of the selected portion of the video frame, such as luminance, prior to quantization to preserve the small detail. During the color-shifting operation, the values of at least one color component of pixels representing the video frame are shifted such that the pixels extend between at least two quantization levels when quantized. In this manner, small detail is preserved, while also allowing for a reduction in the total bits of information contained in the video frame.
    • 讨论了视频处理系统和用于保存正在进行量化的视频中的小细节的方法。 通过识别视频帧内的感兴趣区域来确定小细节,确定视频帧的所选部分内是否存在小细节,并且进一步确定在量化期间这些小细节是否可能丢失。 在视频帧的所选部分中存在小细节并且可能在量化期间丢失的情况下,可以对视频帧的所选部分的一个或多个颜色分量执行色彩转换操作,诸如亮度, 在量化之前保存小细节。 在色彩变换操作期间,表示视频帧的像素的至少一个颜色分量的值被移位,使得像素在量化时在至少两个量化级之间延伸。 以这种方式,保留了细节,同时还允许减少包含在视频帧中的信息的总比特。