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    • 1. 发明授权
    • Image processing device, image processing method and storage medium
    • 图像处理装置,图像处理方法和存储介质
    • US08744199B2
    • 2014-06-03
    • US12903838
    • 2010-10-13
    • Masaki HiragaToshiki ShiinoAkira FujibayashiChoong Seng Boon
    • Masaki HiragaToshiki ShiinoAkira FujibayashiChoong Seng Boon
    • G06K9/36
    • G06T5/002G06T2207/20012H04N7/0132
    • An image processing device includes: processing pixel group determination unit that determines a to-be-processed pixel group from a plurality of frame images of picture signals input based on a first predetermined rule and that determines a processed pixel group from the processed frame image stored based on a second predetermined rule; frequency component processing unit that extracts at least a temporal frequency component from the to-be-processed pixel group and the processed pixel group, that executes predetermined coefficient processing on a temporal high-frequency component of the temporal frequency component and that acquires the executed to-be-processed pixel group; processing completion frame generation unit that generates a processing completion frame image from the executed to-be-processed pixel group; and image output unit that outputs the processing completion frame image and that stores the processing completion frame image in the processed frame storage unit, in which the frequency component processing unit prevents the predetermined coefficient processing from being executed on a component having low sensitivity in visual characteristic included in the temporal high-frequency component.
    • 一种图像处理装置,包括:处理像素组确定单元,其根据第一预定规则从输入的图像信号的多个帧图像中确定待处理像素组,并且从所处理的帧图像确定经处理的像素组 基于第二预定规则; 频率分量处理单元,其从所述被处理像素组和所处理的像素组中提取至少一个时间频率分量,所述处理像素组对所述时间频率分量的时间高频分量执行预定系数处理,并且获取所执行的 被处理的像素组; 处理完成帧生成单元,其从所执行的被处理像素组生成处理完成帧图像; 以及图像输出单元,其输出处理完成帧图像并将处理完成帧图像存储在处理帧存储单元中,其中,频率分量处理单元防止对视觉特性具有低灵敏度的分量执行预定系数处理 包括在时间高频分量中。
    • 2. 发明申请
    • Image identification method and imaging apparatus
    • 图像识别方法和成像装置
    • US20100142807A1
    • 2010-06-10
    • US12462869
    • 2009-08-11
    • Yasuyo YasudaTetsuya HamadaTakashi SuzukiMasaki HiragaYasushi TanaseToshiki Shiino
    • Yasuyo YasudaTetsuya HamadaTakashi SuzukiMasaki HiragaYasushi TanaseToshiki Shiino
    • G06K9/34
    • G06K9/00624G06K9/4642H04N5/232
    • An image identification method for classifying block images of input image data into one of the multiple predetermined categories according to feature quantity in each block image; the method includes an image production step of dividing image data into multiple blocks to produce block images, an image feature quantity processing step of processing the feature quantity of each block image by their color space information and frequency component, a separating hyperplane processing step of learning separating hyperplanes that indicate boundaries of each category by reading in training data image that have labeled categories for each block and processing image feature quantity for each block of an training data image, and a category classification step of classifying respective block image to a category according to the distance from the separating hyperplane of each category by executing the block image production step and the image feature quantity processing step for a newly acquired image to obtain the image feature quantity of block images.
    • 一种图像识别方法,用于根据每个块图像中的特征量将输入图像数据的块图像分类成多个预定类别中的一个; 该方法包括图像产生步骤,将图像数据分割成多个块以产生块图像;图像特征量处理步骤,通过其颜色空间信息和频率分量来处理每个块图像的特征量;分离超平面处理步骤,学习 通过读取具有每个块的标记类别的训练数据图像和训练数据图像的每个块的处理图像特征量来分离指示每个类别的边界的超平面,以及类别分类步骤,根据 通过对新获取的图像执行块图像生成步骤和图像特征量处理步骤来获得每个类别的分离超平面的距离,以获得块图像的图像特征量。
    • 3. 发明授权
    • Image identification method and imaging apparatus
    • 图像识别方法和成像装置
    • US08363933B2
    • 2013-01-29
    • US12462869
    • 2009-08-11
    • Yasuyo YasudaTetsuya HamadaTakashi SuzukiMasaki HiragaYasushi TanaseToshiki Shiino
    • Yasuyo YasudaTetsuya HamadaTakashi SuzukiMasaki HiragaYasushi TanaseToshiki Shiino
    • G06K9/00G06K9/34
    • G06K9/00624G06K9/4642H04N5/232
    • An image identification method for classifying block images of input image data into one of predetermined categories; the method includes the steps of: dividing image data into multiple blocks to produce block images, processing the feature quantity of each block image by their color space information and frequency component, learning separating hyperplanes that indicate boundaries of each category by reading in training data image that have labeled categories for each block and processing image feature quantity for each block of an training data image, and classifying respective block image to a category according to the distance from the separating hyperplane of each category for a newly acquired image to obtain the image feature quantity of block images. An imaging apparatus implementing the image identification method noted above is also disclosed.
    • 一种用于将输入图像数据的块图像分类为预定类别之一的图像识别方法; 该方法包括以下步骤:将图像数据划分成多个块以产生块图像,通过其颜色空间信息和频率分量来处理每个块图像的特征量,通过读取训练数据图像来学习分离表示每个类别的边界的超平面 对于每个块具有标记的类别并且针对训练数据图像的每个块处理图像特征量,并且根据与新获取的图像的每个类别的分离超平面的距离将各个块图像分类到类别以获得图像特征 块图像的数量。 还公开了实现上述图像识别方法的成像装置。
    • 4. 发明授权
    • Apparatus and program for producing a panoramic image
    • 用于生成全景图像的装置和程序
    • US08588546B2
    • 2013-11-19
    • US12220300
    • 2008-07-23
    • Kensuke HabukaMasaki Hiraga
    • Kensuke HabukaMasaki Hiraga
    • G06K9/36G06K9/32
    • H04N1/3876
    • A panoramic image producing apparatus provides an intensity image production unit which produces intensity images from an input source image captured by an imaging device, a reference image data storage unit for storing a reference image which is used to compute the motion data of the intensity image and its absolute motion data, an absolute motion data calculation unit which uses the intensity image of the target image by first computing its relative motion data with respect to the reference image and using its result to compute the absolute motion data with respect to the target image, an image stitching unit to produce a panoramic image by using the absolute motion data computed above to stitch together the input source images, and a reference image setting unit which sets the target image as the new reference image under certain conditions.
    • 全景图像产生装置提供强度图像生成单元,其从由成像装置拍摄的输入源图像产生强度图像,参考图像数据存储单元,用于存储用于计算强度图像的运动数据的参考图像;以及 其绝对运动数据,绝对运动数据计算单元,其通过首先计算其相对于参考图像的相对运动数据并使用其结果来计算相对于目标图像的绝对运动数据来使用目标图像的强度图像, 图像拼接单元,用于通过使用上述计算的绝对运动数据将输入源图像拼接在一起而产生全景图像;以及参考图像设置单元,其在某些条件下将目标图像设置为新的参考图像。
    • 5. 发明申请
    • Object shape exploration using topology matching
    • 使用拓扑匹配的对象形状探索
    • US20050002571A1
    • 2005-01-06
    • US10838320
    • 2004-05-05
    • Masaki HiragaYoshihisa Shinagawa
    • Masaki HiragaYoshihisa Shinagawa
    • G06T7/00G06F17/30G06K9/00G06K9/46G06K9/68G06T7/60
    • G06K9/469G06F16/9024G06K9/00201G06K9/6892
    • A shape analyzer is provided. The analyzer inputs a 3D representation of an object such as merchandise. The structural graph of the object is constructed by defining a continuous function on the surface of the object. The surface is then partitioned into plural areas according to the function values at the points on the surface. The areas are associated with nodes of the graph. By choosing a function that returns values invariant to rotation of the objects, the constructed graph also becomes invariant to rotation. This feature is important when searching for objects by shape from a shape database, as the postures of the objects are unknown when searched for. The analyzer is applicable to search engines for online shopping, where a user seeks goods by designating the general shape of the target.
    • 提供形状分析仪。 分析仪输入物品(例如商品)的3D表示。 对象的结构图通过在对象的表面上定义连续函数来构造。 然后根据表面上的点的功能值将表面分割成多个区域。 这些区域与图形的节点相关联。 通过选择一个函数返回对对象的旋转不变的值,构造的图也变为不变的旋转。 当从形状数据库中按形状搜索对象时,此功能很重要,因为对象的姿势在搜索时是未知的。 分析器适用于搜索引擎的在线购物,其中用户通过指定目标的一般形状来寻找商品。
    • 7. 发明授权
    • Image processing method and imaging apparatus
    • 图像处理方法和成像装置
    • US08224116B2
    • 2012-07-17
    • US12655320
    • 2009-12-29
    • Masaki HiragaKensuke HabukaTakeshi Miura
    • Masaki HiragaKensuke HabukaTakeshi Miura
    • G06K9/40
    • G06T5/002G06T5/20G06T7/13G06T2207/20012G06T2207/20016G06T2207/20192
    • An image processing method for reducing noise of an image to be filtered; the method includes a step of creating shrunken image of shrinking ratio r×r (where r is a natural number) by averaging the pixel values for each pixel in a block for every r pixels, a step of obtaining the pixel value in the shrunken image that correspond to the focus pixel in the source image by performing linear interpolation from the shrunken image pixels, a step of determining the noise reduction filter from the focus pixel and reference pixel in the shrunken image, and a step of computing the compensated pixel value of the focus pixel in the source image by weighted sum of each pixel value applying the filter to the focus pixel in the source image and the corresponding shrunken pixel.
    • 一种用于降低要滤波的图像的噪声的图像处理方法; 该方法包括通过对每个r个像素的块中的每个像素的像素值进行平均来创建缩小率r×r(其中r是自然数)的缩小图像的步骤,获得缩小图像中的像素值的步骤 通过从缩小图像像素执行线性插值,对应于源图像中的焦点像素的步骤,从缩小图像中的聚焦像素和参考像素确定降噪滤波器的步骤,以及计算补偿像素值的步骤 源图像中的焦点像素通过将滤光器应用于源图像中的焦点像素和相应的缩小像素的每个像素值的加权和。
    • 8. 发明授权
    • Motion vector calculation method and hand-movement correction device, imaging device and moving picture generation device
    • 运动矢量计算方法和手动校正装置,成像装置和运动图像生成装置
    • US07847823B2
    • 2010-12-07
    • US11795218
    • 2005-01-14
    • Kensuke HabukaMasaki Hiraga
    • Kensuke HabukaMasaki Hiraga
    • H04N5/228H04N5/14H04N9/64
    • G06T7/20
    • A motion vector calculation method includes: processing for calculating multi-resolution data up to a predetermined resolution level L from a plurality of inputted image data; and processing for estimating motion vectors per resolution executing a matching step for temporarily calculating motion vectors minimizing an energy function within a predetermined range of the input motion vectors and a smoothing step for finally calculating the motion vectors by averaging the surrounding data. By using the motion vectors of the resolution level L finally calculated as input motion vectors of a further higher resolution level L-1, the processing for estimating motion vectors per resolution is successively repeated on image data of a high resolution, thereby calculating the motion vectors.
    • 一种运动矢量计算方法,包括:从多个输入图像数据计算高达预定分辨率电平L的多分辨率数据的处理; 以及用于估计每个分辨率的运动矢量的处理,执行用于临时计算在输入运动矢量的预定范围内最小化能量函数的运动矢量的匹配步骤,以及平滑步骤,用于通过对周围数据求平均来最终计算运动矢量。 通过使用最终计算为更高分辨率电平L-1的输入运动矢量的分辨率电平L的运动矢量,对高分辨率的图像数据连续重复用于估计每分辨率的运动矢量的处理,从而计算运动矢量 。