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    • 3. 发明授权
    • Picture/graphics classification system and method
    • 图片/图形分类系统和方法
    • US06983068B2
    • 2006-01-03
    • US09965922
    • 2001-09-28
    • Salil PrabhakarHui ChengZhigang FanJohn C. HandleyYing-wei Lin
    • Salil PrabhakarHui ChengZhigang FanJohn C. HandleyYing-wei Lin
    • G06K9/00
    • G06K9/00456
    • A method and system for image processing, in conjunction with classification of images between natural pictures and synthetic graphics, using SGLD texture (e.g., variance, bias, skewness, and fitness), color discreteness (e.g., R—L, R—U, and R—V normalized histograms), or edge features (e.g., pixels per detected edge, horizontal edges, and vertical edges) is provided. In another embodiment, a picture/graphics classifier using combinations of SGLD texture, color discreteness, and edge features is provided. In still another embodiment, a “soft” image classifier using combinations of two (2) or more SGLD texture, color discreteness, and edge features is provided. The “soft” classifier uses image features to classify areas of an input image in picture, graphics, or fuzzy classes.
    • 一种用于图像处理的方法和系统,结合使用SGLD纹理(例如,方差,偏差,偏度和适应度)的自然图像和合成图像之间的图像分类,颜色离散性(例如,R SUB 提供了一个或多个边缘特征(例如每个检测到的边缘,水平边缘和垂直边缘的像素)。 在另一个实施例中,提供了使用SGLD纹理,颜色离散性和边缘特征的组合的图片/图形分类器。 在另一个实施例中,提供了使用两(2)或更多SGLD纹理,颜色离散性和边缘特征的组合的“软”图像分类器。 “软”分类器使用图像特征来对图像,图形或模糊类中的输入图像的区域进行分类。
    • 8. 发明授权
    • Reducing smear and slow response artifacts in vector error diffusion
    • US09848105B1
    • 2017-12-19
    • US09080700
    • 1998-05-18
    • Zhigang Fan
    • Zhigang Fan
    • H04N1/405H04N1/60G06K15/02
    • H04N1/4052G06K15/1881H04N1/52H04N1/6027
    • A method of color image processing for quantizing output includes obtaining an input for an object pixel which is represented by a vector in a first color space. A modified input equal to the input plus a sum of errors from other pixels in a neighborhood of the object pixel is generated. For each color component in the first color space, where corresponding color components of the modified input are located with respect to a preset range is determined. If the modified input's color component is greater than the preset range, then that color component for an output is determined to be on; if less than the preset range, then that color component for the output is determine to be off; and, if within the preset range, then that color component for the output is determined to be unknown. A transformed modified input is mapped to a perceptual color space when any color component of the output is unknown. Colors consistent with color components of the output that have already been determined are also mapped to the perceptual color space. The color in the perceptual color space that lies closest to the transformed modified input is chosen. An output in the first color space having color components on and off is generated consistent with the determinations and/or choices made. Error for the object pixel is then calculated as the difference between the output and the modified input.
    • 9. 发明申请
    • IMAGE CAPTURE BY SCENE CLASSIFICATION
    • 通过场景分类的图像捕获
    • US20160286114A1
    • 2016-09-29
    • US15081281
    • 2016-03-25
    • Zhigang Fan
    • Zhigang Fan
    • H04N5/235H04N5/232G02B7/28G06T5/00G06T5/20G06K9/46G06K9/62G06T7/00
    • H04N5/2352G02B7/285G06K9/4661G06K9/6267H04N5/23212
    • A method, a device and a computer readable for automatically identifying a Christmas tree scene and setting a camera's focus and/or exposure parameters in a way that yields images with high image quality. The Christmas tree scene identification can be performed by segmenting the image into bright and dark regions, identifying the light objects, collecting the statistics of the light objects, and classifying the scene based on the statistics of the light objects, or by collecting the pixel value statistics for the image, and classifying the scene based on the statistics of the pixel values, or by collecting the pixel value statistics for the image, filtering the image, collecting the pixel value statistics for the filtered image, and classifying the scene by comparing the statistics of the pixel values before and after filtering. The focus and exposure settings can be adjusted based on the Christmas tree scene identification results. For Christmas tree scenes, the exposure can be set based on a value that is adjusted upwards from the mean luminance of the image, or on a value that is calculated from the top luminance value. The focus can be set by identifying the lights in the image, and minimizing the light size in the image.
    • 用于自动识别圣诞树场景并以产生具有高图像质量的图像的方式设置相机的焦点和/或曝光参数的方法,设备和计算机。 可以通过将图像分割成明暗区域,识别光对象,收集光对象的统计数据和基于光对象的统计信息对场景进行分类,或者通过收集像素值来执行圣诞树场景识别 统计图像,并根据像素值的统计信息对场景进行分类,或者通过收集图像的像素值统计信息,过滤图像,收集滤波图像的像素值统计数据,并对场景进行分类比较 过滤前后像素值的统计。 焦点和曝光设置可以根据圣诞树场景识别结果进行调整。 对于圣诞树场景,可以基于从图像的平均亮度向上调整的值或从顶部亮度值计算的值来设置曝光。 可以通过识别图像中的光,并最小化图像中的光线大小来设置焦点。