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    • 1. 发明授权
    • Appearance inspecting method
    • 外观检查方法
    • US5319720A
    • 1994-06-07
    • US913190
    • 1992-07-14
    • Haruhiko YokoyamaMasaya Nakao
    • Haruhiko YokoyamaMasaya Nakao
    • G01B11/24G06T1/00G06T7/00G06K9/00
    • G06T7/0006G06T2207/10024G06T2207/30148
    • An appearance inspecting method includes the steps of dividing a recognized image of an object into regions based on two attributes of image points within the image calculating the minimum distance of each point within a target region to a periphery of the target region, and measuring a size of the target region from the maximum of the calculated minimum distances of the points in the target region. A distance measuring method for measuring a distance of each point within a region to a periphery of the region includes the steps of dividing each region to be measured by lines made of picture elements arranged in one direction, sequentially integrating the distance of each point from the periphery of the region from its outer side to a middle point in each line from one end line to the other end line of the region to thereby obtain the minimum distance of each point, and the distance of each point from the periphery of the region is sequentially integrated from its outer side to the middle point in each line from the other end line to the one end line of the region to thereby obtain the minimum distance of each point.
    • 外观检查方法包括以下步骤:基于图像内的图像点的两个属性,将目标区域中的每个点的最小距离计算到目标区域的周边,将目标的识别图像划分为区域,并且测量尺寸 从目标区域中的点的计算出的最小距离的最大值来计算目标区域。 用于测量区域内的每个点到该区域的周边的距离的距离测量方法包括以下步骤:将由沿一个方向布置的像素组成的线划分成待测量的每个区域,依次将从每个点的距离 该区域的边缘从该区域的一端线到另一端线的每条线的外侧至中点,从而获得每个点的最小距离,并且每个点与该区域的周边的距离为 从其另一端线到该区域的一端的每条线从其外侧到中点顺序地集成,从而获得每个点的最小距离。
    • 3. 发明授权
    • Dot pattern-examining apparatus
    • 点阵图案检查装置
    • US5570298A
    • 1996-10-29
    • US249164
    • 1994-05-25
    • Noriyuki SuzukiHaruhiko Yokoyama
    • Noriyuki SuzukiHaruhiko Yokoyama
    • G06K9/46G06F17/00
    • G06K9/4647
    • A dot pattern-examining apparatus examines a dot pattern displayed on a display screen by picking up a two-dimensional image of the display screen and by performing image processing with respect to the dot pattern on the two-dimensional image. An image projection data generating section generates image projection data indicative of a set of density values by accumulating, on a predetermined axis, density values of individual dots of the two-dimensional image of the display screen for each line. Then, a run-length data generating section generates run-length data indicative of a set of combinations of an accumulated density value and a length thereof, based on the image projection data of the two-dimensional image. Thereafter, a run-length data matching section compares the run-length data of the two-dimensional image with a reference run-length data indicating a reference dot pattern and generated in advance by the run-length data generating section, to thereby determine a position having run-length data which most match the reference run-length data as the position where the dot pattern to be examined exists.
    • 点阵图案检查装置通过拾取显示屏幕的二维图像并且对二维图像上的点图案执行图像处理,来检查显示在显示屏幕上的点阵图形。 图像投影数据生成部通过在规定的轴上累积各行的显示画面的二维图像的各个点的浓度值来生成表示浓度值的图像投影数据。 然后,游程长度数据生成部基于二维图像的图像投影数据生成指示累积浓度值和其长度的组合的游程长度数据。 此后,游程长度数据匹配部分将二维图像的游程长度数据与指示参考点图案的参考游程长度数据进行比较,并由游程长度数据生成部分预先生成,从而确定 具有与参考游程长度数据最匹配的游程长度数据作为要被检查的点图案的位置的位置。
    • 4. 发明授权
    • Object inspection method employing selection of discerning features
using mahalanobis distances
    • 使用马哈拉诺比斯距离选择识别特征的对象检查方法
    • US5392364A
    • 1995-02-21
    • US885837
    • 1992-05-20
    • Haruhiko YokoyamaMasaya Nakao
    • Haruhiko YokoyamaMasaya Nakao
    • G06K9/46G06K9/62G06K9/64G06T1/00G06T7/40G06K9/68
    • G06K9/64
    • A method for discerning whether an object to be inspected is acceptable or not is based on feature values with respect to a binary-coded image of the object. The method includes the steps of coding image data of the object into binary digits to obtain the binary-coded image, calculating at least three feature values based on a predetermined sample group of acceptable objects and a predetermined sample group of unacceptable objects, obtaining a Mahalanobis' generalized distance between the sample groups of the acceptable objects and the unacceptable objects with respect to each of the calculated feature values, comparing each of the distances with a first predetermined value and then selecting as a first representative feature value the distance which is not smaller than the first predetermined value, obtaining a Mahalanobis' generalized distance between groups of acceptable objects and unacceptable objects with respect to the feature values except for the feature value selected as the first representative feature value and the first representative feature value, and comparing each of the distances with a second predetermined value and then selecting as a second representative feature value the distance which is not smaller than the second predetermined value, so that it is discerned whether the object is acceptable or not based on the first and/or first and second feature values with respect to the binary-coded image of the object.
    • 用于识别被检查对象是否可接受的方法是基于关于对象的二进制编码图像的特征值。 该方法包括以下步骤:将对象的图像数据编码为二进制数字以获得二进制编码图像,基于可接受对象的预定样本组和预定的不可接受对象样本组计算至少三个特征值,获得马氏距离 相对于所计算的每个特征值,可接受对象的样本组和不可接受对象之间的广义距离,将每个距离与第一预定值进行比较,然后将不等于的距离选择为第一代表特征值 相对于除了选择为第一代表特征值和第一代表特征值的特征值之外的特征值,获得可接受物体组和不可接受物体之间的马氏距离广义距离,并且比较第一预定值, 距离与第二预定值然后 选择不小于第二预定值的距离作为第二代表特征值,使得基于相对于二进制编码的第一和/或第一和第二特征值来辨别对象是否可接受 对象的形象。
    • 8. 发明授权
    • Image processing method for distinguishing object by determining
threshold of image lightness values
    • 通过确定图像亮度值的阈值来区分对象的图像处理方法
    • US5138671A
    • 1992-08-11
    • US613983
    • 1990-11-14
    • Haruhiko Yokoyama
    • Haruhiko Yokoyama
    • G06T1/00G06K9/38G06T5/40
    • G06K9/38G06T7/0081G06T2207/20148
    • An image processing method distinguishes an object from within an image area by determining a stable threshold value of light intensity values from within the image area. Received light is converted into image data denoting light intensity values of the received light at a plurality of points from within the image area. A bright portion average value denoting an average of the light intensity values which exceed a predetermined threshold and a dark portion average value denoting an average of the light intensity values which are less than the predetermined threshold are calculated. A new threshold is obtained by applying the bright portion average value and the dark portion average value to a predetermined dividing ratio. The object within the image area is distinguished using the new threshold. The method is also applicable to the use of multivalue thresholds.
    • 图像处理方法通过从图像区域内确定光强度值的稳定阈值来区分图像区域内的对象。 接收的光被转换成表示来自图像区域内的多个点处的接收光的光强度值的图像数据。 计算表示超过预定阈值的光强度值的平均值的亮部分平均值和表示小于预定阈值的光强度值的平均值的暗部平均值。 通过将亮度部分平均值和暗部平均值应用到预定的分频比来获得新的阈值。 使用新阈值区分图像区域内的对象。 该方法也适用于使用多值阈值。