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    • 1. 发明申请
    • SYSTEM OR METHOD FOR IDENTIFYING A REGION-OF-INTEREST IN AN IMAGE
    • 用于识别图像中的利益区域的系统或方法
    • WO2005027047A3
    • 2006-04-27
    • PCT/IB2004002922
    • 2004-09-08
    • EATON CORPFARMER MICHAEL ECHEN XUNCHANGWEN LI
    • FARMER MICHAEL ECHEN XUNCHANGWEN LI
    • G06T7/00G06K9/32G06T5/00G06T7/20
    • 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“下划线”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。
    • 3. 发明申请
    • SYSTEM OR METHOD FOR CLASSIFYING IMAGES
    • 用于分类图像的系统或方法
    • WO2005008581A3
    • 2005-04-14
    • PCT/IB2004002347
    • 2004-07-20
    • EATON CORPFARMER MICHAEL ECHEN XUNCHANG
    • FARMER MICHAEL ECHEN XUNCHANG
    • B60R21/01G06K9/00
    • G06K9/00832G06K9/00362
    • A system or method is disclosed for classifying sensor images into one of several pre-defined classifications (22). Mathematical moments (72) relating to various features (74) or attributes in the sensor image (26) are used to populated a vector of attributes (28), which are then compared to a corresponding template vector of attribute values (87). The template vector (87) contains values for known classifications (22) which are preferably predefined. By comparing the two vectors, various votes (92) and confidence metrics (85) are used to ultimately selct the appropriate classification (22). In some embodiments, preparation processing is performed before loading the attribute vector (87) with values. Image segmentation (69) is often desirable. The performance of heuristics (73) to adjust for environmental factors such as lighting can also be desirable. One embodiment of the system (29) is to prevent the deployment of an airbag when the occupant (34) in the seat (36) is a child, a rearfacing infant seat (36), or when the seat (36) is empty.
    • 公开了一种用于将传感器图像分类成几个预定义分类(22)中的一个的系统或方法。 使用与传感器图像(26)中的各种特征(74)或属性有关的数学矩(72)来填充属性向量(28),然后将其与属性值(87)的对应模板向量进行比较。 模板矢量(87)包含优选预定义的已知分类(22)的值。 通过比较这两个向量,使用各种投票(92)和置信度度量(85)来最终选择适当的分类(22)。 在一些实施例中,在向属性向量(87)加载值之前执行准备处理。 图像分割(69)通常是可取的。 启发式(73)调整环境因素(如照明)的性能也是可取的。 系统(29)的一个实施例是当座椅(36)中的乘客(34)是儿童,面向后方的婴儿座椅(36)或座椅(36)为空时防止气囊展开。