公开(公告)号：US20100200660A1

公开(公告)日：2010-08-12

申请号：US12703077

申请日：2010-02-09

申请人： Michael C. Moed ,  Mikhail Akopyan

发明人： Michael C. Moed ,  Mikhail Akopyan

IPC分类号： G06K7/10

CPC分类号： G06K7/14

摘要： This invention provides a system and method for capturing, detecting and extracting features of an ID, such as a 1D barcode, that employs an efficient processing system based upon a CPU-controlled vision system on a chip (VSoC) architecture, which illustratively provides a linear array processor (LAP) constructed with a single instruction multiple data (SIMD) architecture in which each pixel of the rows of the pixel array are directed to individual processors in a similarly wide array. The pixel data are processed in a front end (FE) process that performs rough finding and tracking of regions of interest (ROIs) that potentially contain ID-like features. The ROI-finding process occurs in two parts so as to optimize the efficiency of the LAP in neighborhood operations—a row-processing step that occurs during image pixel readout from the pixel array and an image-processing step that occurs typically after readout occurs. The relative motion of the ID-containing ROI with respect to the pixel array is tracked and predicted. An optional back end (BE) process employs the predicted ROI to perform feature-extraction after image capture. The feature extraction derives candidate ID features that are verified by a verification step that confirms the ID, creates a refined ROI, angle of orientation and feature set. These are transmitted to a decoding processor or other device.

摘要翻译： 本发明提供了一种用于捕获，检测和提取诸如1D条形码的ID的特征的系统和方法，其采用基于CPU控制的芯片（VSoC）架构上的视觉系统的有效处理系统，其示意性地提供 线性阵列处理器（LAP），其使用单个指令多数据（SIMD）架构构造，其中像素阵列的行中的每个像素以类似的宽阵列定向到各个处理器。 在前端（FE）处理中对像素数据进行处理，其执行可能包含类ID特征的感兴趣区域（ROI）的粗略查找和跟踪。 ROI寻找过程发生在两个部分中，以便在邻域操作中优化LAP的效率 - 在从像素阵列读出图像像素期间发生的行处理步骤和通常在读出后出现的图像处理步骤。 跟踪并预测含有ID的ROI相对于像素阵列的相对运动。 可选的后端（BE）过程使用预测的ROI在图像捕获之后执行特征提取。 特征提取导出通过确认ID的验证步骤验证的候选ID特征，创建精确的ROI，定向角度和特征集。 这些被发送到解码处理器或其他设备。

公开(公告)号：US09189670B2

公开(公告)日：2015-11-17

申请号：US12703077

申请日：2010-02-09

申请人： Michael C. Moed ,  Mikhail Akopyan

发明人： Michael C. Moed ,  Mikhail Akopyan

IPC分类号： G06K7/14

CPC分类号： G06K7/14

摘要： This invention provides a system and method for capturing, detecting and extracting features of an ID, such as a 1D barcode, that employs an efficient processing system based upon a CPU-controlled vision system on a chip (VSoC) architecture, which illustratively provides a linear array processor (LAP) constructed with a single instruction multiple data (SIMD) architecture in which each pixel of the rows of the pixel array are directed to individual processors in a similarly wide array. The pixel data are processed in a front end (FE) process that performs rough finding and tracking of regions of interest (ROIs) that potentially contain ID-like features. The ROI-finding process occurs in two parts so as to optimize the efficiency of the LAP in neighborhood operations—a row-processing step that occurs during image pixel readout from the pixel array and an image-processing step that occurs typically after readout occurs. The relative motion of the ID-containing ROI with respect to the pixel array is tracked and predicted. An optional back end (BE) process employs the predicted ROI to perform feature-extraction after image capture. The feature extraction derives candidate ID features that are verified by a verification step that confirms the ID, creates a refined ROI, angle of orientation and feature set. These are transmitted to a decoding processor or other device.

摘要翻译： 本发明提供了一种用于捕获，检测和提取诸如1D条形码的ID的特征的系统和方法，其采用基于CPU控制的芯片（VSoC）架构上的视觉系统的有效处理系统，其示意性地提供 线性阵列处理器（LAP），其使用单个指令多数据（SIMD）架构构造，其中像素阵列的行中的每个像素以类似的宽阵列定向到各个处理器。 在前端（FE）处理中对像素数据进行处理，其执行可能包含类ID特征的感兴趣区域（ROI）的粗略查找和跟踪。 ROI寻找过程发生在两个部分中，以便在邻域操作中优化LAP的效率 - 在从像素阵列读出图像像素期间发生的行处理步骤和通常在读出后出现的图像处理步骤。 跟踪并预测含有ID的ROI相对于像素阵列的相对运动。 可选的后端（BE）过程使用预测的ROI在图像捕获之后执行特征提取。 特征提取导出通过确认ID的验证步骤验证的候选ID特征，创建精确的ROI，定向角度和特征集。 这些被发送到解码处理器或其他设备。

公开(公告)号：US06973207B1

公开(公告)日：2005-12-06

申请号：US09451084

申请日：1999-11-30

申请人： Mikhail Akopyan ,  Lowell Jacobson ,  Lei Wang

发明人： Mikhail Akopyan ,  Lowell Jacobson ,  Lei Wang

IPC分类号： G06K9/00 ,  G06K9/64 ,  G06T7/00

CPC分类号： G06T7/0004 ,  G06K9/6206 ,  G06K9/6211

摘要： An embodiment of the invention provides a method for training a system to inspect a spatially distorted pattern. A digitized image of an object, including a region of interest, is received. The region of interest is further divided in to a plurality of sub-regions. A size of each of the sub-regions is small enough such that a conventional inspecting method can reliably inspect each of the sub-regions. A search tool and an inspecting tool are trained for a respective model for each of the sub-regions. A search tree is built for determining an order for inspecting the sub-regions. A coarse alignment tool is trained for the region of interest. Another embodiment of the invention provides a method for inspecting a spatially distorted pattern. A coarse alignment tool is run to approximately locate a pattern. Search tree information and an approximate location of a root image, found by the coarse alignment tool, is used to locate sub-regions sequentially in an order according to the search tree information. Each of the sub-regions is inspected, the sub regions being small enough such that a conventional inspecting method can reliably inspect each of the sub-regions.

摘要翻译： 本发明的实施例提供了一种用于训练系统以检查空间变形图案的方法。 接收包括感兴趣区域的对象的数字化图像。 感兴趣区域进一步被划分为多个子区域。 每个子区域的尺寸足够小，使得常规的检查方法可以可靠地检查每个子区域。 针对每个子区域的相应模型训练搜索工具和检查工具。 构建搜索树来确定检查子区域的顺序。 针对感兴趣的区域训练粗对准工具。 本发明的另一实施例提供了一种用于检查空间变形图案的方法。 运行粗略对齐工具以大致定位图案。 搜索树信息和由粗对准工具找到的根图像的大致位置用于根据搜索树信息按顺序依次定位子区域。 每个子区域被检查，子区域足够小，使得常规检查方法可以可靠地检查每个子区域。