公开(公告)号：US06631215B1

公开(公告)日：2003-10-07

申请号：US09448009

申请日：1999-11-23

申请人： Jeng-nan Shiau ,  Raymond J. Clark ,  Stuart A. Schweid ,  Terri A. Clingerman

发明人： Jeng-nan Shiau ,  Raymond J. Clark ,  Stuart A. Schweid ,  Terri A. Clingerman

IPC分类号： G06K940

CPC分类号： G06T5/20

摘要： A method and apparatus are provided for determining a weighted average measured reflectance parameter Rm for pixels in an image for use in integrated cavity effect correction of the image. For each pixel of interest Pi,j in the image, an approximate spatial dependent average Ai,j, Bi,j of video values in a region of W pixels by H scan lines surrounding the pixel of interest Pi,j is computed by convolving video values Vi,j of the image in the region with a uniform filter. For each pixel of interest Pi,j a result of the convolving step is used as the reflectance parameter Rm. The apparatus includes a video buffer for storing the pixels of the original scanned image, and first and second stage average buffers for storing the computed approximate spatial dependent averages Ai,j, Bi,j. First and second stage processing circuits respectively generate the first and second stage average values Ai,j, Bi,j by convolving the video values of the image in a preselected region with a uniform filter.

摘要翻译： 提供一种方法和装置，用于确定用于图像的集成腔效应校正的图像中的像素的加权平均测量反射率参数Rm。 对于图像中的每个感兴趣像素P i，j，通过卷积视频来计算在围绕像素p，j的W像素的H像素的区域中的视频值的近似空间依赖平均值Ai，j，Bi，j 在具有均匀滤波器的区域中的图像的值Vi，j。 对于感兴趣的每个像素Pi，j，使用卷积步骤的结果作为反射参数Rm。 该装置包括用于存储原始扫描图像的像素的视频缓冲器，以及用于存储所计算的近似空间相关平均值Ai，j，Bi，j的第一和第二平均缓冲器。 第一和第二级处理电路通过使用均匀的滤波器卷积预选区域中的图像的视频值，分别产生第一和第二平均值Ai，j，Bi，j。

公开(公告)号：US06525845B1

公开(公告)日：2003-02-25

申请号：US09234107

申请日：1999-01-19

申请人： Gaurav Sharma ,  Stuart A. Schweid ,  Jeng-Nan Shiau

发明人： Gaurav Sharma ,  Stuart A. Schweid ,  Jeng-Nan Shiau

IPC分类号： H04N146

CPC分类号： H04N1/00015 ,  H04N1/00002 ,  H04N1/00037 ,  H04N1/00087 ,  H04N1/2315 ,  H04N1/40062

摘要： Image information is re-calibrated based on the type of marking process and materials by which the image corresponding to the image information was marked on a substrate. The marking process is automatically detected by using, for example, at least one spatial characteristic obtained from the image information.

摘要翻译： 基于标记处理的类型和与图像信息对应的图像在基板上标记的材料重新校准图像信息。 通过使用例如从图像信息获得的至少一个空间特性来自动检测标记处理。

公开(公告)号：US5765029A

公开(公告)日：1998-06-09

申请号：US646540

申请日：1996-05-08

申请人： Stuart A. Schweid ,  Jeng-Nan Shiau ,  Raymond J. Clark

发明人： Stuart A. Schweid ,  Jeng-Nan Shiau ,  Raymond J. Clark

IPC分类号： G06T5/20 ,  G06T7/40 ,  H04N1/40 ,  G06F9/44 ,  G06K9/46

CPC分类号： G06T7/403 ,  H04N1/40062 ,  Y10S706/90

摘要： A method and system electronically fuzzy classify a pixel belonging to a set of digital image data with respect to a membership of the pixel in a plurality of image classes. This process determines a fuzzy classification of the pixel and generates an effect tag for the pixel based on the fuzzy classification determination. Each class is defined by a set of heuristic rules such that the image classes are non-mutually exclusive. The heuristic rules are a set of conditions that define the membership value of the pixel within a certain class, thereby allowing a pixel to have a membership value in every possible image class.

摘要翻译： 电子模糊方法和系统相对于多个图像类别中的像素的隶属度来归类属于一组数字图像数据的像素。 该过程确定像素的模糊分类，并且基于模糊分类确定为像素生成效应标签。 每个类由一组启发式规则定义，使得图像类是非互斥的。 启发式规则是一组条件，用于定义某个类中像素的隶属度值，从而允许像素在每个可能的图像类中具有隶属值。

公开(公告)号：US06529291B1

公开(公告)日：2003-03-04

申请号：US09401378

申请日：1999-09-22

申请人： Stuart A. Schweid ,  Jeng-nan Shiau ,  Zhigang Fan

发明人： Stuart A. Schweid ,  Jeng-nan Shiau ,  Zhigang Fan

IPC分类号： G06F1500

CPC分类号： H04N1/6025

摘要： A color conversion table designed to produce 0% under-color removal and a 100% under-color removal TRC are configured as a matched pair and are used to render an image from fuzzy detected color signals, including providing variable under-color removal to obtain fuzzy black conversion. The output of the color conversion table and the TRC are multiplied by a weighted value which depends on a value of a received neutral tag. The weighted outputs of the color conversion table and TRC are added such that a varying weighted output is generated. The generated output is used in image rendering to produce a smooth transition from a full color to monochrome, where variable amounts of under-color removal are obtained using the color correction table and TRC.

摘要翻译： 被设计为产生0％的底色去除和100％底色去除TRC的颜色转换表被配置为匹配对，并且用于从模糊检测到的颜色信号渲染图像，包括提供可变的底色去除以获得 模糊黑转换。 颜色转换表和TRC的输出乘以取决于所接收的中立标签的值的加权值。 添加颜色转换表和TRC的加权输出，使得生成变化的加权输出。 生成的输出用于图像渲染，以产生从全色到单色的平滑过渡，其中使用颜色校正表和TRC获得可变量的底色去除。

公开(公告)号：US07421143B2

公开(公告)日：2008-09-02

申请号：US10709832

申请日：2004-06-01

申请人： Xing Li ,  Stuart A. Schweid ,  Jeng-nan Shiau

发明人： Xing Li ,  Stuart A. Schweid ,  Jeng-nan Shiau

IPC分类号： G06K9/40

CPC分类号： H04N1/40062 ,  H04N1/4072

摘要： A method for dynamic range adjustment of image data of a captured image by determining a white point of an image. The method also involves determining a black point of the image, classifying pixels of the image, and determining an offset value for a pixel of the image based on the determined black point of the image and the determined classification of the pixel. Dynamic range adjustment of the image data is performed using the determined offset value for the pixels of the image and the determined white point of the image.

摘要翻译： 通过确定图像的白点来对拍摄图像的图像数据进行动态范围调整的方法。 该方法还包括确定图像的黑点，对图像的像素进行分类，以及基于确定的图像的黑点和所确定的像素的分类来确定图像的像素的偏移值。 使用确定的图像的像素的偏移值和确定的图像的白点来执行图像数据的动态范围调整。

公开(公告)号：US06535633B1

公开(公告)日：2003-03-18

申请号：US09405712

申请日：1999-09-24

申请人： Stuart A. Schweid ,  Jeng-nan Shiau

发明人： Stuart A. Schweid ,  Jeng-nan Shiau

IPC分类号： G06K900

CPC分类号： H04N1/56 ,  G06T7/11 ,  G06T2207/10024 ,  G06T2207/30176 ,  H04N1/40062

摘要： A method and apparatus are provided for use in single channel segmentation of color images for reclassifying pixels which were inappropriately classified as belonging to a “black” or “white” class. The apparatus includes a re-classification circuit receiving first classification data generated by a single channel segmentation circuit operative to classify pixels of a multi-color channel input image. The re-classification circuit selectively re-classifies pixels that were previously classified by the single channel segmentation circuit into an “other” segmentation class based on a comparison of classification data associated with the pixels relative to a set of predefined classification data types. Particularly, the re-classification circuit reclassifies selected ones of the pixels into the “other” segmentation class when first classification data generated by the single channel segmentation circuit labels the pixels as a “white” or “black” data type.

摘要翻译： 提供了一种用于彩色图像的单通道分割的方法和装置，用于将不适当地归类为属于“黑色”或“白色”类的像素重新分类。 该装置包括接收由单通道分割电路生成的第一分类数据的再分类电路，其操作以对多色信道输入图像的像素进行分类。 重新分类电路基于与相对于一组预定义分类数据类型的像素相关联的分类数据的比较，有选择地将先前由单个信道分割电路分类的像素重新分类为“其他”分割类别。 特别地，当由单个信道分割电路产生的第一分类数据将像素标记为“白色”或“黑色”数据类型时，重新分类电路将所选择的像素重新分类为“其他”分割类别。

公开(公告)号：US06947597B2

公开(公告)日：2005-09-20

申请号：US09965880

申请日：2001-09-28

申请人： Ying-wei Lin ,  Stuart A. Schweid ,  Jeng-nan Shiau ,  Raja Bala ,  Zhigang Fan

发明人： Ying-wei Lin ,  Stuart A. Schweid ,  Jeng-nan Shiau ,  Raja Bala ,  Zhigang Fan

IPC分类号： G06K9/20 ,  G06T5/00 ,  H04N1/40 ,  G06K9/62

CPC分类号： H04N1/40062 ,  G06K9/00456

摘要： 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.

摘要翻译： 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_L，R_U和R_V归一化直方图 ）或边缘特征（例如，每个检测到的边缘的像素，水平边缘和垂直边缘）。 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。

公开(公告)号：US06549658B1

公开(公告)日：2003-04-15

申请号：US09010371

申请日：1998-01-21

申请人： Stuart A. Schweid ,  Jeng-Nan Shiau

发明人： Stuart A. Schweid ,  Jeng-Nan Shiau

IPC分类号： G06K934

CPC分类号： H04N1/40062 ,  G06K9/00456

摘要： A system and method classify a pixel of image data as one of a plurality of image types. A first image characteristic value for the pixel, a second image characteristic value for the pixel, a third image characteristic value for the pixel, and a fourth image characteristic for the pixel is determined. Some of these determinations may be resolution dependent. The values from these determination are utilized in assigning an image type classification to the pixel. Moreover, if at least one of the image characteristic values is greater than a predetermined threshold value the pixel is classified as a halftone peak value. The system includes a plurality of microclassifiers for determining a distinct image characteristic value of the pixel; a plurality of macroreduction circuits connected to the plurality of microclassifiers for performing further higher level operations upon the distinct image characteristic values of the pixel to produce reduced values; and a classification circuit to classify the pixel as an image type based on the reduced values from the macroreduction circuits. The system also includes a circuit to detect flat peaks without detecting multiple peaks and a rectangular blur filtering system.

摘要翻译： 系统和方法将图像数据的像素分类为多个图像类型之一。 确定像素的第一图像特征值，像素的第二图像特征值，像素的第三图像特征值和用于像素的第四图像特性。 这些确定中的一些可能取决于分辨率。 来自这些确定的值被用于为像素分配图像类型分类。 此外，如果图像特征值中的至少一个大于预定阈值，则将像素分类为半色调峰值。 该系统包括用于确定像素的不同图像特征值的多个微分类器; 连接到所述多个微分类器的多个宏观还原电路，用于根据所述像素的不同图像特征值进行更高级的操作以产生减小的值; 以及分类电路，用于基于来自大致减小电路的减小值将像素分类为图像类型。 该系统还包括用于检测平坦峰而不检测多个峰的电路和矩形模糊滤波系统。

公开(公告)号：US06181829B2

公开(公告)日：2001-01-30

申请号：US09010331

申请日：1998-01-21

申请人： Raymond J. Clark ,  Leon C. Williams ,  Stuart A. Schweid ,  Jeng-Nan Shiau

发明人： Raymond J. Clark ,  Leon C. Williams ,  Stuart A. Schweid ,  Jeng-Nan Shiau

IPC分类号： G06K940

CPC分类号： H04N1/40062

摘要： A system and method classify a pixel of image data as one of a plurality of image types. A first image characteristic value for the pixel, a second image characteristic value for the pixel ,a third image characteristic value for the pixel, and a fourth image characteristic for the pixel is determined. Some of these determinations may be resolution dependent. The values from these determination are utilized in assigning an image type classification to the pixel. Moreover, if at least one of the image characteristic values is greater than a predetermined threshold value the pixel is classified as a halftone peak value. The system includes a plurality of microclassifiers for determining a distinct image characteristic value of the pixel; a plurality of macroreduction circuits connected to the plurality of microclassifiers for performing further higher level operations upon the distinct image characteristic values of the pixel to produce reduced values; and a classification circuit to classify the pixel as an image type based on the reduced values from the macroreduction circuits. The system also includes a circuit to detect flat peaks without detecting multiple peaks and a rectangular blur filtering system.

摘要翻译： 系统和方法将图像数据的像素分类为多个图像类型之一。 确定像素的第一图像特征值，像素的第二图像特征值，像素的第三图像特征值和用于像素的第四图像特性。 这些确定中的一些可能取决于分辨率。 来自这些确定的值被用于为像素分配图像类型分类。 此外，如果图像特征值中的至少一个大于预定阈值，则将像素分类为半色调峰值。 该系统包括用于确定像素的不同图像特征值的多个微分类器; 连接到所述多个微分类器的多个宏观还原电路，用于根据所述像素的不同图像特征值进行更高级的操作以产生减小的值; 以及分类电路，用于基于来自大致减小电路的减小值将像素分类为图像类型。 该系统还包括用于检测平坦峰而不检测多个峰的电路和矩形模糊滤波系统。

公开(公告)号：US09798712B2

公开(公告)日：2017-10-24

申请号：US13609541

申请日：2012-09-11

申请人： Beilei Xu ,  Stuart A. Schweid ,  Raja Bala ,  Rinku Gajera

发明人： Beilei Xu ,  Stuart A. Schweid ,  Raja Bala ,  Rinku Gajera

IPC分类号： G06F5/16 ,  G06F17/24 ,  G06F17/28

CPC分类号： G06F17/248 ,  G06F17/289

摘要： The present disclosure provides a method of producing a personalized medical record, comprising: sensing capabilities of a receiving device; retrieving stock information; retrieving personalized information; combining at least a portion of the stock information and at least a portion of the personalized information into the personalized record; formatting the personalized record based on a combination of the capabilities of the receiving device and a user's preference; and, transmitting the formatted personalized record to the device.