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1.发明授权Method and system for coding information on a roadway surface subject to motion blur 失效用于对运动模糊的道路表面上的信息进行编码的方法和系统公开(公告)号：US08378799B2
公开(公告)日：2013-02-19
申请号：US12640949
申请日：2009-12-17
申请人： Raymond Yim , Samuel David Perli , Fatih Porikli , Jinyun Zhang
发明人： Raymond Yim , Samuel David Perli , Fatih Porikli , Jinyun Zhang
IPC分类号： G08B21/00
CPC分类号： G06K7/14 , G06K7/1417 , G06K7/1473
摘要： Symbols in information are encoded as a codeword using a differential orthogonal code. The codeword is stored in a substrate. A moving sensor acquires an image of the codeword in the substrate and decodes the codeword using a balanced differential decoder. The codeword can be painted as lane markings on a road surface.
摘要翻译： 使用差分正交码将信息中的符号编码为码字。 码字被存储在基板中。 移动传感器获取衬底中的码字的图像，并使用平衡差分解码器解码码字。 码字可以作为道路表面上的车道标记来绘制。
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公开(公告)号：US20100327064A1
公开(公告)日：2010-12-30
申请号：US12640949
申请日：2009-12-17
申请人： Raymond Yim , Samuel David Perli , Fatih Porikli , Jinyun Zhang
发明人： Raymond Yim , Samuel David Perli , Fatih Porikli , Jinyun Zhang
CPC分类号： G06K7/14 , G06K7/1417 , G06K7/1473
摘要： Symbols in information are encoded as a codeword using a differential orthogonal code. The codeword is stored in a substrate. A moving sensor acquires an image of the codeword in the substrate and decodes the codeword using a balanced differential decoder. The codeword can be painted as lane markings on a road surface.
摘要翻译： 使用差分正交码将信息中的符号编码为码字。 码字被存储在基板中。 移动传感器获取衬底中的码字的图像，并使用平衡差分解码器解码码字。 码字可以作为道路表面上的车道标记来绘制。
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公开(公告)号：US09076227B2
公开(公告)日：2015-07-07
申请号：US13632500
申请日：2012-10-01
申请人： Fatih Porikli , Feng Li
发明人： Fatih Porikli , Feng Li
CPC分类号： G06T7/277 , G06T2207/10076 , G06T2207/10124 , G06T2207/10136 , G06T2207/20076 , G06T2207/20081 , G06T2207/30096
摘要： A tumor is tracked in multiple sequences of images acquired concurrently from different viewpoints. Features are extracted in each set of current images using a window. A regression function, subject to motion constraints, is applied to the features to obtain 3D motion parameters, which are applied to the tumor as observed in the images to obtain a 3D location of the object. Then, the shape of the 3D object at the 3D location is projected onto each image to update the location of the window for the next set of images to be processed.
摘要翻译： 以不同观点同时获得的多个图像序列跟踪肿瘤。 使用窗口在每组当前图像中提取特征。 受到运动约束的回归函数被应用于特征以获得3D运动参数，其被应用于在图像中观察到的肿瘤以获得对象的3D位置。 然后，将3D位置处的3D对象的形状投影到每个图像上，以更新要处理的下一组图像的窗口的位置。
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公开(公告)号：US08433148B2
公开(公告)日：2013-04-30
申请号：US13076522
申请日：2011-03-31
申请人： Fatih Porikli
发明人： Fatih Porikli
摘要： A method compresses an image partitioned into blocks of pixels, for each block the method converts the block to a 2D matrix. The matrix is decomposing into a column matrix and a row matrix, wherein a width of the column matrix is substantially smaller than a height of the column matrix and the height of the row matrix is substantially smaller than the width of the row matrix. The column matrix and the row matrix are compressed, and the compressed matrices are then combined to form a compressed image.
摘要翻译： 一种方法将分割成像素块的图像压缩，对于每个块，该方法将块转换为2D矩阵。 矩阵分解为列矩阵和行矩阵，其中列矩阵的宽度基本上小于列矩阵的高度，并且行矩阵的高度基本上小于行矩阵的宽度。 列矩阵和行矩阵被压缩，然后将压缩的矩阵组合以形成压缩图像。
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公开(公告)号：US20120250933A1
公开(公告)日：2012-10-04
申请号：US13075822
申请日：2011-03-30
申请人： Fatih Porikli , Mohamed Hussein
发明人： Fatih Porikli , Mohamed Hussein
IPC分类号： G06K9/34
CPC分类号： G06K9/6224 , G06T7/11 , G06T7/143 , G06T7/162 , G06T7/174 , G06T7/194 , G06T2207/10136 , G06T2207/20156 , G06T2207/30096
摘要： A tumor is tracked in sequences of biplane images by generating a set of segmentation hypotheses using a 3D model of the tumor, a biplane geometry, and a previous location of the tumor as determined from the pairs of biplane images. Volume prior probabilities are constructed based on the set of hypotheses. Seed pixels are selected using the volume prior probabilities, and a bi-plane dual image graph is constructed using intensity gradients and the seed pixels to obtaining segmentation masks corresponding to tumor boundaries using the image intensities to determine a current location of the tumor.
摘要翻译： 通过使用从双平面图像对确定的肿瘤的3D模型，双平面几何形状和肿瘤的先前位置生成一组分割假设来跟踪双平面图像的序列。 体积先验概率是基于一组假设构建的。 使用体积先验概率选择种子像素，并且使用强度梯度和种子像素构建双平面双图像图像，以使用图像强度获得对应于肿瘤边界的分割掩模，以确定肿瘤的当前位置。
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6.发明申请公开(公告)号：US20060177131A1
公开(公告)日：2006-08-10
申请号：US11052598
申请日：2005-02-07
申请人： Fatih Porikli
发明人： Fatih Porikli
IPC分类号： G06K9/00
CPC分类号： G06T7/20 , G06F17/18 , G06K9/4642 , G06K9/6212 , G06T2207/10016 , G06T2207/30201
摘要： A computer implemented method extracts an integral histogram from sampled data, such as time series data, images, and volumetric data. First, a set of samples is acquired from a real-word signal. The set of samples is scanned in a predetermined order. For each current sample, an integral histogram integrating a histogram of the current sample and integral histograms of previously scanned samples is constructed.
摘要翻译： 计算机实现的方法从诸如时间序列数据，图像和体积数据的采样数据中提取积分直方图。 首先，从真实字信号中获取一组样本。 以预定的顺序扫描该组样本。 对于每个当前样本，构建一个集成了当前样本的直方图和先前扫描样本的积分直方图的积分直方图。
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公开(公告)号：US20060078205A1
公开(公告)日：2006-04-13
申请号：US10961926
申请日：2004-10-08
申请人： Fatih Porikli , Jie Shao
发明人： Fatih Porikli , Jie Shao
IPC分类号： G06K9/46
CPC分类号： G06K9/0063 , G03B15/006 , G06K9/6292
摘要： A method detects roads in an aerial image of ground topology by determining low-level features, such as intensities and gradients, for each pixel in the aerial image, determining middle-level features, such as an orientation for each pixel from the low-level features, and determining high-level features from the middle-level features. Each high-level feature is assigned a probability, and the probabilities of the high-level features for each pixel are normalized and aggregated to a single probability that the pixel is associated with a road.
摘要翻译： 一种方法通过确定空中图像中每个像素的低级特征（如强度和梯度）来检测地面拓扑的空中图像中的道路，确定中间层特征，例如来自低层的每个像素的取向 功能，并确定中级功能的高级功能。 每个高级特征被分配概率，并且将每个像素的高级特征的概率归一化并聚合成像素与道路相关联的单一概率。
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公开(公告)号：US08942467B2
公开(公告)日：2015-01-27
申请号：US13428554
申请日：2012-03-23
申请人： Fatih Porikli , Yi Wang
发明人： Fatih Porikli , Yi Wang
IPC分类号： G06K9/62
摘要： Blocking artifacts are reduced by projecting each patch obtained from an input image onto a set of bases vectors to determine multiple representations for each patch. The set of bases vectors are learned from a training image, and the bases vectors include a full basis vector, and one or two subspace bases vectors. An optimal basis vector is determined in the set of bases vectors for each patch according to the projection. A threshold is applied to coefficients of the optimal basis vector to determine a filtered representation for each patch, and a reconstructed patch is generated using the filtered representation. Then, the aggregating the reconstructed patches are aggregated to produce an output image.
摘要翻译： 通过将从输入图像获得的每个贴片投影到一组基本矢量上以确定每个贴片的多个表示来减少阻挡伪影。 从训练图像中学习基本矢量集合，并且基本矢量包括全基矢量和一个或两个子空间基矢量。 根据投影，在每个贴片的基准矢量集合中确定最优基矢量。 将阈值应用于最佳基本矢量的系数，以确定每个贴片的滤波表示，并且使用滤波后的表示生成重建的贴片。 然后，聚合重建的片段被聚合以产生输出图像。
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公开(公告)号：US20130251245A1
公开(公告)日：2013-09-26
申请号：US13428554
申请日：2012-03-23
申请人： Fatih Porikli , Yi Wang
发明人： Fatih Porikli , Yi Wang
摘要： Blocking artifacts are reduced by projecting each patch obtained from an input image onto a set of bases vectors to determine multiple representations for each patch. The set of bases vectors are learned from a training image, and the bases vectors include a full basis vector, and one or two subspace bases vectors. An optimal basis vector is determined in the set of bases vectors for each patch according to the projection. A threshold is applied to coefficients of the optimal basis vector to determine a filtered representation for each patch, and a reconstructed patch is generated using the filtered representation. Then, the aggregating the reconstructed patches are aggregated to produce an output image.
摘要翻译： 通过将从输入图像获得的每个贴片投影到一组基本矢量上以确定每个贴片的多个表示来减少阻挡伪影。 从训练图像中学习基本矢量集合，并且基本矢量包括全基矢量和一个或两个子空间基矢量。 根据投影，在每个贴片的基准矢量集合中确定最优基矢量。 将阈值应用于最佳基本矢量的系数，以确定每个贴片的滤波表示，并且使用滤波后的表示生成重建的贴片。 然后，聚合重建的片段被聚合以产生输出图像。
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公开(公告)号：US20130223734A1
公开(公告)日：2013-08-29
申请号：US13405155
申请日：2012-02-24
申请人： Oncel Tuzel , Fatih Porikli , Chinmay Hegde
发明人： Oncel Tuzel , Fatih Porikli , Chinmay Hegde
CPC分类号： G06T3/4053
摘要： A natural input image is upscaled, first by interpolation. Second, edges in the interpolated image are sharpened by a lion-parametric patch transform. The result is decomposed into an edge layer and a detail layer. Only pixels in the detail layer enhanced, and the enhanced detail layer is merged with the edge layer to produce a high resolution version of the input image.
摘要翻译： 自然输入图像放大，首先通过插值。 第二，插值图像中的边缘通过狮子参数补丁变换来锐化。 结果被分解成边缘层和细节层。 只有细节层中的像素增强，并且增强的细节层与边缘层合并以产生输入图像的高分辨率版本。
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