Text Image Quality Based Feedback For Improving OCR
    71.
    发明申请
    Text Image Quality Based Feedback For Improving OCR 有权
    基于文本图像质量的反馈改进OCR

    公开(公告)号:US20140168478A1

    公开(公告)日:2014-06-19

    申请号:US13843637

    申请日:2013-03-15

    CPC classification number: G06K9/2054 G06K9/2081 G06K9/3258 G06K2209/01

    Abstract: An electronic device and method capture multiple images of a scene of real world at a several zoom levels, the scene of real world containing text of one or more sizes. Then the electronic device and method extract from each of the multiple images, one or more text regions, followed by analyzing an attribute that is relevant to OCR in one or more versions of a first text region as extracted from one or more of the multiple images. When an attribute has a value that meets a limit of optical character recognition (OCR) in a version of the first text region, the version of the first text region is provided as input to OCR.

    Abstract translation: 电子设备和方法以几个缩放级别捕获真实世界场景的多个图像,现实世界的场景包含一个或多个尺寸的文本。 然后,电子设备和方法从多个图像中的每一个提取一个或多个文本区域,随后从多个图像中的一个或多个提取出的第一文本区域的一个或多个版本中分析与OCR相关的属性 。 当属性具有满足第一文本区域的版本中的光学字符识别(OCR)限制的值时,第一文本区域的版本被提供作为OCR的输入。

    Method of Perspective Correction For Devanagari Text
    72.
    发明申请
    Method of Perspective Correction For Devanagari Text 有权
    梵文文本视角校正方法

    公开(公告)号:US20140161365A1

    公开(公告)日:2014-06-12

    申请号:US13842985

    申请日:2013-03-15

    CPC classification number: G06K9/00469 G06K9/3283 G06K2009/363 G06K2209/01

    Abstract: An electronic device and method identify regions that are likely to be text in a natural image or video frame, followed by processing as follows: lines that are nearly vertical are automatically identified in a selected text region, oriented relative to the vertical axis within a predetermined range −max_theta to +max_theta, followed by determination of an angle θ of the identified lines, followed by use of the angle θ to perform perspective correction by warping the selected text region. After perspective correction in this manner, each text region is processed further, to recognize text therein, by performing OCR on each block among a sequence of blocks obtained by slicing the potential text region. Thereafter, the result of text recognition is used to display to the user, either the recognized text or any other information obtained by use of the recognized text.

    Abstract translation: 电子设备和方法识别可能是自然图像或视频帧中的文本的区域,随后如下处理:在所选择的文本区域中自动识别几乎垂直的行,所述文本区域相对于预定的 范围-max_theta到+ max_theta,然后确定角度和角度; 的确定线,然后使用角度和角度; 通过扭曲所选择的文本区域来执行透视校正。 在以这种方式进行透视校正之后,通过对通过切割潜在文本区域获得的块序列中的每个块执行OCR,进一步处理每个文本区域以识别其中的文本。 此后,文本识别的结果用于向用户显示识别的文本或通过使用识别的文本获得的任何其他信息。

    IDENTIFYING REGIONS OF TEXT TO MERGE IN A NATURAL IMAGE OR VIDEO FRAME
    73.
    发明申请
    IDENTIFYING REGIONS OF TEXT TO MERGE IN A NATURAL IMAGE OR VIDEO FRAME 有权
    在自然图像或视频框架中识别文本区域

    公开(公告)号:US20130195315A1

    公开(公告)日:2013-08-01

    申请号:US13748539

    申请日:2013-01-23

    Abstract: In several aspects of described embodiments, an electronic device and method use a camera to capture an image or a frame of video of an environment outside the electronic device followed by identification of blocks of regions in the image. Each block that contains a region is checked, as to whether a test for presence of a line of pixels is met. When the test is met for a block, that block is identified as pixel-line-present. Pixel-line-present blocks are used to identify blocks that are adjacent. One or more adjacent block(s) may be merged with a pixel-line-present block when one or more rules are found to be satisfied, resulting in a merged block. The merged block is then subject to the above-described test, to verify presence of a line of pixels therein, and when the test is satisfied the merged block is processed normally, e.g. classified as text or non-text.

    Abstract translation: 在所描述的实施例的几个方面中,电子设备和方法使用相机来捕获电子设备外的环境的图像或视频帧,随后识别图像中的区域块。 检查包含区域的每个块,以确定是否满足一行像素的存在测试。 当块的测试被满足时,该块被标识为像素线存在。 像素线呈现块用于识别相邻的块。 当发现满足一个或多个规则时,一个或多个相邻块可以与像素线存在块合并,导致合并块。 然后,合并的块经过上述测试,以验证其中的一行像素的存在,并且当满足测试时,合并的块被正常处理,例如, 分类为文本或非文本。

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