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    • 4. 发明申请
    • Image adjustment derived from optical imaging measurement data
    • 从光学成像测量数据导出的图像调整
    • US20080055543A1
    • 2008-03-06
    • US11511651
    • 2006-08-29
    • Scott MeyerXunchang ChenRodney P. Chin
    • Scott MeyerXunchang ChenRodney P. Chin
    • A61B3/10
    • A61B3/102A61B3/113
    • A method and apparatus for imaging within the eye is provided whereby a component of eye position is detected using optical imaging data. Tracking eye position over time and correctly registering imaging data for scan locations or using eye position to detect decentration achieves improved imaging. In one embodiment, essentially perpendicular B-scans are imaged sequentially and the corneal arc within each B-scan is analyzed to determine the vertex of the eye. The eye vertex is tracked over pairs of perpendicular B-scans to determine eye motion. In another embodiment, the decentration in the Pachymetry map is removed by correcting for the misalignment of the center of the Pachymetry map and the actual location of the corneal vertex.
    • 提供一种用于眼内成像的方法和装置,由此使用光学成像数据检测眼睛位置的分量。 随着时间的推移跟踪眼睛位置并正确记录扫描位置的成像数据或使用眼睛位置来检测偏心,实现了改善的成像。 在一个实施例中,基本上垂直的B扫描被顺序成像,并且分析每个B扫描内的角膜弧以确定眼睛的顶点。 通过成对的垂直B扫描来跟踪眼睛顶点以确定眼睛运动。 在另一个实施例中,通过校正Pachymetry图的中心和角膜顶点的实际位置的偏移来去除Pachymetry图中的偏心。
    • 5. 发明申请
    • System or method for classifying images
    • 用于分类图像的系统或方法
    • US20050271280A1
    • 2005-12-08
    • US10625208
    • 2003-07-23
    • Michael FarmerXunchang Chen
    • Michael FarmerXunchang Chen
    • B60R21/01G06K9/00G06K9/62
    • G06K9/00832G06K9/00362
    • A system or method (collectively “classification system”) is disclosed for classifying sensor images into one of several pre-defined classifications. Mathematical moments relating to various features or attributes in the sensor image are used to populated a vector of attributes, which are then compared to a corresponding template vector of attribute values. The template vector contains values for known classifications which are preferably predefined. By comparing the two vectors, various votes and confidence metrics are used to ultimately select the appropriate classification. In some embodiments, preparation processing is performed before loading the attribute vector with values. Image segmentation is often desirable. The performance of heuristics to adjust for environmental factors such as lighting can also be desirable. One embodiment of the system is to prevent the deployment of an airbag when the occupant in the seat is a child, a rear-facing infant seat, or when the seat is empty.
    • 公开了一种用于将传感器图像分类为若干预定义分类之一的系统或方法(统称为“分类系统”)。 与传感器图像中的各种特征或属性相关的数学时刻用于填充属性向量,然后将其与属性值的相应模板向量进行比较。 模板向量包含优选预定义的已知分类的值。 通过比较两个向量,使用各种投票和置信度量度来最终选择合适的分类。 在一些实施例中,在使用值加载属性向量之前执行准备处理。 图像分割通常是可取的。 启发式调整对照明等环境因素的表现也是可取的。 该系统的一个实施例是当座椅中的乘客是儿童,面向后方的婴儿座椅时或当座椅空着时防止安全气囊展开。
    • 9. 发明申请
    • System or method for identifying a region-of-interest in an image
    • 用于识别图像中感兴趣区域的系统或方法
    • US20050058322A1
    • 2005-03-17
    • US10663521
    • 2003-09-16
    • Michael FarmerLi WenXunchang Chen
    • Michael FarmerLi WenXunchang Chen
    • G06K9/32G06T5/00G06T7/20G06K9/00G06K9/34
    • G06K9/3233G06T7/11G06T7/155G06T2207/10048G06T2207/20132G06T2207/20152G06T2207/30252
    • The disclosed segmentation method and system (collectively “system”) identifies a region-of-interest within an ambient image captured by a sensor. The ambient image includes the target image (the “segmented image” of the target), as well as the area surrounding the target. The disclosed system purposely “under-segments” the ambient image, and the process is typically followed by a subsequent segmentation process to remove the portions of the region-of-interest image that do not represent the segmented image. The system compares the ambient image captured by the sensor with a template ambient image without a target to assist in identifying the region-of-interest. They system performs a watershed heuristic to further remove portions of the ambient image from the region-of-interest. In a safety restraint embodiment of the system, the region-of-interest can be used by the safety restrain application to determine the classification of the vehicle occupant, and motion characteristics relating to the occupant.
    • 公开的分割方法和系统(统称为“系统”)识别由传感器捕获的环境图像内的感兴趣区域。 环境图像包括目标图像(目标的“分割图像”)以及目标周围的区域。 所公开的系统有意地“环绕”环境图像,并且该过程通常后跟随后的分割处理以去除不表示分割图像的感兴趣区域图像的部分。 该系统将传感器捕获的环境图像与模板环境图像进行比较,而无需目标,以帮助识别感兴趣的区域。 他们系统执行分水岭启发式,以进一步从感兴趣的区域中去除环境图像的部分。 在系统的安全约束实施例中,安全限制应用可以使用感兴趣区域来确定车辆乘员的分类以及与乘客相关的运动特性。