Visual pattern recognition in an image
    41.
    发明授权
    Visual pattern recognition in an image 有权
    图像中的视觉模式识别

    公开(公告)号:US09141885B2

    公开(公告)日:2015-09-22

    申请号:US13953394

    申请日:2013-07-29

    CPC classification number: G06K9/627 G06K9/4642

    Abstract: A system may be configured as an image recognition machine that utilizes an image feature representation called local feature embedding (LFE). LFE enables generation of a feature vector that captures salient visual properties of an image to address both the fine-grained aspects and the coarse-grained aspects of recognizing a visual pattern depicted in the image. Configured to utilize image feature vectors with LFE, the system may implement a nearest class mean (NCM) classifier, as well as a scalable recognition algorithm with metric learning and max margin template selection. Accordingly, the system may be updated to accommodate new classes with very little added computational cost. This may have the effect of enabling the system to readily handle open-ended image classification problems.

    Abstract translation: 系统可以被配置为利用称为局部特征嵌入(LFE)的图像特征表示的图像识别机器。 LFE能够生成捕获图像的显着视觉特性的特征向量,以解决识别图像中描绘的视觉图案的细粒度方面和粗粒度方面。 配置为利用具有LFE的图像特征向量,系统可以实现最近的等级均值(NCM)分类器,以及具有度量学习和最大边距模板选择的可缩放识别算法。 因此,可以更新系统以容纳新类别,而且增加了很少的计算成本。 这可能具有使系统能够容易地处理开放式图像分类问题的效果。

    Adaptive patch-based image upscaling
    42.
    发明授权
    Adaptive patch-based image upscaling 有权
    基于自适应补片的图像放大

    公开(公告)号:US09123138B2

    公开(公告)日:2015-09-01

    申请号:US13920911

    申请日:2013-06-18

    CPC classification number: G06T3/40 G06T3/4076

    Abstract: Image upscaling techniques are described. These techniques may include use of iterative and adjustment upscaling techniques to upscale an input image. A variety of functionality may be incorporated as part of these techniques, examples of which include content-adaptive patch finding techniques that may be employed to give preference to an in-place patch to minimize structure distortion. In another example, content metric techniques may be employed to assign weights for combining patches. In a further example, algorithm parameters may be adapted with respect to algorithm iterations, which may be performed to increase efficiency of computing device resource utilization and speed of performance. For instance, algorithm parameters may be adapted to enforce a minimum and/or maximum number to iterations, cease iterations for image sizes over a threshold amount, set sampling step sizes for patches, employ techniques based on color channels (which may include independence and joint processing techniques), and so on.

    Abstract translation: 描述了图像升高技术。 这些技术可以包括使用迭代和调整放大技术来升高输入图像。 作为这些技术的一部分,可以并入各种功能,其示例包括可用于优先使用就地补丁以最小化结构失真的内容自适应补片发现技术。 在另一示例中,可以采用内容度量技术来分配用于组合补丁的权重。 在另一示例中,算法参数可以针对算法迭代进行调整,这可以被执行以提高计算设备资源利用率和性能的效率。 例如,算法参数可以适于对迭代执行最小和/或最大数量,停止针对阈值量的图像大小的迭代,设置用于补丁的采样步长,采用基于颜色通道的技术(其可以包括独立性和联合 处理技术)等。

    TEXT DETECTION IN NATURAL IMAGES
    43.
    发明申请
    TEXT DETECTION IN NATURAL IMAGES 有权
    自然图像中的文本检测

    公开(公告)号:US20150055857A1

    公开(公告)日:2015-02-26

    申请号:US13970993

    申请日:2013-08-20

    CPC classification number: G06K9/18 G06K9/3258

    Abstract: A system and method of text detection in an image are described. A component detection module applies a filter having a stroke width constraint and a stroke color constraint to an image to identify text stroke pixels in the image and to generate both a first map based on the stroke width constraint and a second map based on the stroke color constraint. A component filtering module has a first classifier and second classifier. The first classifier is applied to both the first map and the second map to generate a third map identifying a component of a text in the image. The second classifier is applied to the third map to generate a fourth map identifying a text line of the text in the image. A text region locator module thresholds the fourth map to identify text regions in the image.

    Abstract translation: 描述图像中文本检测的系统和方法。 分量检测模块将具有笔划宽度约束和笔画颜色约束的滤波器应用于图像以识别图像中的文本笔划像素,并且基于笔画宽度约束生成第一地图,并且基于笔画颜色生成第二地图 约束。 组件过滤模块具有第一分类器和第二分类器。 将第一分类器应用于第一地图和第二地图,以生成标识图像中的文本的分量的第三映射。 将第二分类器应用于第三图,以生成标识图像中的文本的文本行的第四图。 文本区域定位器模块阈值第四个映射以识别图像中的文本区域。

    Image enhancement using self-examples and external examples

    公开(公告)号:US10198801B2

    公开(公告)日:2019-02-05

    申请号:US15392162

    申请日:2016-12-28

    Abstract: Systems and methods are provided for image enhancement using self-examples in combination with external examples. In one embodiment, an image manipulation application receives an input image patch of an input image. The image manipulation application determines a first weight for an enhancement operation using self-examples and a second weight for an enhancement operation using external examples. The image manipulation application generates a first interim output image patch by applying the enhancement operation using self-examples to the input image patch and a second interim output image patch by applying the enhancement operation using external examples to the input image patch. The image manipulation application generates an output image patch by combining the first and second interim output image patches as modified using the first and second weights.

    Searching untagged images with text-based queries

    公开(公告)号:US10042866B2

    公开(公告)日:2018-08-07

    申请号:US14788113

    申请日:2015-06-30

    Abstract: In various implementations, a personal asset management application is configured to perform operations that facilitate the ability to search multiple images, irrespective of the images having characterizing tags associated therewith or without, based on a simple text-based query. A first search is conducted by processing a text-based query to produce a first set of result images used to further generate a visually-based query based on the first set of result images. A second search is conducted employing the visually-based query that was based on the first set of result images received in accordance with the first search conducted and based on the text-based query. The second search can generate a second set of result images, each having visual similarity to at least one of the images generated for the first set of result images.

    Patch partitions and image processing

    公开(公告)号:US09978129B2

    公开(公告)日:2018-05-22

    申请号:US15707418

    申请日:2017-09-18

    Abstract: Patch partition and image processing techniques are described. In one or more implementations, a system includes one or more modules implemented at least partially in hardware. The one or more modules are configured to perform operations including grouping a plurality of patches taken from a plurality of training samples of images into respective ones of a plurality of partitions, calculating an image processing operator for each of the partitions, determining distances between the plurality of partitions that describe image similarity of patches of the plurality of partitions, one to another, and configuring a database to provide the determined distance and the image processing operator to process an image in response to identification of a respective partition that corresponds to a patch taken from the image.

    Image tagging
    49.
    发明授权

    公开(公告)号:US09607014B2

    公开(公告)日:2017-03-28

    申请号:US14068238

    申请日:2013-10-31

    CPC classification number: G06F17/30265 G06K9/6263 G06K2209/27

    Abstract: A system is configured to annotate an image with tags. As configured, the system accesses an image and generates a set of vectors for the image. The set of vectors may be generated by mathematically transforming the image, such as by applying a mathematical transform to predetermined regions of the image. The system may then query a database of tagged images by submitting the set of vectors as search criteria to a search engine. The querying of the database may obtain a set of tagged images. Next, the system may rank the obtained set of tagged images according to similarity scores that quantify degrees of similarity between the image and each tagged image obtained. Tags from a top-ranked subset of the tagged images may be extracted by the system, which may then annotate the image with these extracted tags.

    Image enhancement using self-examples and external examples
    50.
    发明授权
    Image enhancement using self-examples and external examples 有权
    图像增强使用自我实例和外部实例

    公开(公告)号:US09569684B2

    公开(公告)日:2017-02-14

    申请号:US14020969

    申请日:2013-09-09

    Abstract: Systems and methods are provided for image enhancement using self-examples in combination with external examples. In one embodiment, an image manipulation application receives an input image patch of an input image. The image manipulation application determines a first weight for an enhancement operation using self-examples and a second weight for an enhancement operation using external examples. The image manipulation application generates a first interim output image patch by applying the enhancement operation using self-examples to the input image patch and a second interim output image patch by applying the enhancement operation using external examples to the input image patch. The image manipulation application generates an output image patch by combining the first and second interim output image patches as modified using the first and second weights.

    Abstract translation: 提供了使用自身实例与外部示例组合的图像增强的系统和方法。 在一个实施例中,图像处理应用接收输入图像的输入图像块。 图像处理应用使用自身示例确定用于增强操作的第一权重,并且使用外部示例来确定用于增强操作的第二权重。 图像处理应用程序通过使用自身示例将增强操作应用于输入图像贴片和第二中期输出图像贴图,通过使用外部示例将输入图像贴图应用增强操作来生成第一临时输出图像贴片。 图像处理应用程序通过组合使用第一和第二权重修改的第一和第二临时输出图像块来生成输出图像块。

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