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1. 发明授权

US09087374B2 Automatic airview correction method 有权
标题翻译：自动风景校正方法
公开(公告)号：US09087374B2
公开(公告)日：2015-07-21
申请号：US13597662
申请日：2012-08-29
申请人： Li-You Hsu , Yu-Sheng Liao , Tzu-Chien Hsu
发明人： Li-You Hsu , Yu-Sheng Liao , Tzu-Chien Hsu
IPC分类号： G06K9/00 , G06T7/00 , G06T3/40
CPC分类号： G06T7/0018 , G06K9/00805 , G06T3/4038 , G06T7/33 , G06T7/80 , G06T2207/30208 , G06T2207/30252
摘要： An automatic airview correction method comprises steps: moving a vehicle to an airview alignment pattern; capturing a plurality of airview alignment images of the surroundings of the vehicle; correcting distortion of the airview alignment images to obtain a plurality of corrected images; performing alignment compensation on the corrected images; searching for corner points of the corrected images and converting view points to obtain a plurality of view angle-converted images; and searching for corner points of the view angle-converted images, and seaming the view angle-converted images to form a panoramic airview and obtain parameters corresponding to the panoramic airview. The present invention can automatically align images and can also automatically detect corner points to seam the images of the surroundings of a vehicle, whereby to form a panoramic airview.
摘要翻译：一种自动风景校正方法，包括以下步骤：将车辆移动到气道对准模式; 捕获车辆周围环境的多个气视对准图像; 校正气视对准图像的失真以获得多个校正图像; 对校正图像执行对准补偿; 搜索校正图像的角点并转换视点以获得多个视角转换图像; 并且搜索视角转换图像的角点，并且将视角转换图像接合以形成全景视野并获得与全景视野对应的参数。本发明可以自动对准图像，还可以自动检测角点以缝合车辆周围的图像，从而形成全景视野。

2. 发明申请

US20130329945A1 SELF-ADAPTIVE IMAGE-BASED OBSTACLE DETECTION METHOD 有权
标题翻译：基于自适应图像的OBSTACLE检测方法
公开(公告)号：US20130329945A1
公开(公告)日：2013-12-12
申请号：US13568824
申请日：2012-08-07
申请人： Chih-Hung YANG , Li-You Hsu
发明人： Chih-Hung YANG , Li-You Hsu
IPC分类号： G06K9/78
CPC分类号： G06K9/00805 , G06K9/00798
摘要： A self-adaptive image-based obstacle detection method comprises steps: capturing an original image; transforming the original image to an HSV color space, and retrieving a hue component (H) and a saturation component (S) of the HSV color space to form an HS-based image; dividing the HS-based image into image blocks; selecting one image block as a background block; using an obstacle recognition equation to determine whether each of the image blocks is similar to the background block; if no, deleting the image block; if yes, preserving the image block to form a binary obstacle image; and overlaying the binary obstacle image on the original image to filter out the background and obtain an initial ambit of an obstacle image. Then, three orderly movement flow equations are used to determine whether it is an obstacle.
摘要翻译：基于自适应图像的障碍物检测方法包括以下步骤：捕获原始图像; 将原始图像变换为HSV颜色空间，以及检索HSV颜色空间的色调分量（H）和饱和度分量（S）以形成基于HS的图像; 将基于HS的图像划分为图像块; 选择一个图像块作为背景块; 使用障碍物识别方程来确定每个图像块是否与背景块相似; 如果没有，删除图像块; 如果是，则保存图像块以形成二进制障碍物图像; 并将二值障碍物图像重叠在原始图像上以滤除背景并获得障碍物图像的初始范围。然后，使用三个有序的运动流动方程来确定它是否是障碍。

3. 发明授权

US08934669B2 Self-adaptive image-based obstacle detection method 有权
标题翻译：自适应图像障碍物检测方法
公开(公告)号：US08934669B2
公开(公告)日：2015-01-13
申请号：US13568824
申请日：2012-08-07
申请人： Chih-Hung Yang , Li-You Hsu
发明人： Chih-Hung Yang , Li-You Hsu
IPC分类号： G06K9/00 , G06K9/34 , G06K9/46 , G06K9/66 , G06K9/36 , G06K9/20
CPC分类号： G06K9/00805 , G06K9/00798
摘要： A self-adaptive image-based obstacle detection method comprises steps: capturing an original image; transforming the original image to an HSV color space, and retrieving a hue component (H) and a saturation component (S) of the HSV color space to form an HS-based image; dividing the HS-based image into image blocks; selecting one image block as a background block; using an obstacle recognition equation to determine whether each of the image blocks is similar to the background block; if no, deleting the image block; if yes, preserving the image block to form a binary obstacle image; and overlaying the binary obstacle image on the original image to filter out the background and obtain an initial ambit of an obstacle image. Then, three orderly movement flow equations are used to determine whether it is an obstacle.
摘要翻译：基于自适应图像的障碍物检测方法包括以下步骤：捕获原始图像; 将原始图像变换为HSV颜色空间，以及检索HSV颜色空间的色调分量（H）和饱和度分量（S）以形成基于HS的图像; 将基于HS的图像划分为图像块; 选择一个图像块作为背景块; 使用障碍物识别方程来确定每个图像块是否与背景块相似; 如果没有，删除图像块; 如果是，则保存图像块以形成二进制障碍物图像; 并将二值障碍物图像重叠在原始图像上以滤除背景并获得障碍物图像的初始范围。然后，使用三个有序的运动流动方程来确定它是否是障碍。

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