公开(公告)号：US20170061227A1

公开(公告)日：2017-03-02

申请号：US15212731

申请日：2016-07-18

Applicant: Tata Consultancy Services Limited

Inventor： Hrishikesh SHARMA ,  Adithya VELLAIAPPAN ,  Balamuralidhar PURUSHOTHAMAN

IPC: G06K9/32 ,  G06K9/62 ,  G06K9/46

CPC classification number: G06K9/3241 ,  G06K9/00637 ,  G06K9/4604 ,  G06K9/6204 ,  G06K9/6218

Abstract: The present disclosure provides systems and methods to enable detection of linear objects such as utility poles in complex and heterogeneous outdoor surroundings. The methods deal with shape and orientation as prominent features of a pole model. Candidate trapeziums from 2D images of the face of the poles are extracted, some of which represent parts of the pole. To overcome the missed detection of certain parts due to problems of occlusion and diffusion into background, shape based techniques, that extrapolate and capture a longer trapezium representing the pole is implemented. The region growing stage or extrapolation is driven by orientation-based clustering of trapeziums. Context information is further used to identify objects of interest, by discarding false positives. Besides detecting poles of interest, the detected poles are further analysed to identify damages, if any.

Abstract translation: 本公开提供了系统和方法，以能够检测线性物体，例如在复杂和异质的室外环境中的电线杆。 该方法将形状和方向作为极模型的突出特征。 提取二极图2D图像中的候选梯形图，其中一些代表极点的一部分。 为了克服由于阻塞和扩散到背景中的问题而导致的某些部分的漏检，实现了外推和捕获代表极点的更长梯形的基于形状的技术。 区域生长阶段或外推是由梯形的基于定向的聚类驱动的。 通过舍弃误报，进一步利用上下文信息来识别感兴趣的对象。 除了检测到感兴趣的极点之外，进一步分析检测到的极点以识别损伤（如果有的话）。

公开(公告)号：US20170068855A1

公开(公告)日：2017-03-09

申请号：US15211654

申请日：2016-07-15

Applicant: Tata Consultancy Services Limited

Inventor： Hrishikesh SHARMA ,  Adithya VELLAIAPPAN ,  Balamuralidhar PURUSHOTHAMAN

IPC: G06K9/00 ,  B64C39/02 ,  B64D47/08 ,  H04N5/247

CPC classification number: G06K9/00577 ,  B64C39/024 ,  B64C2201/123 ,  B64C2201/127 ,  B64D47/08 ,  G06K9/00637 ,  G06K9/4619 ,  H04N5/247

Abstract: This disclosure relates generally to ge visual inspection systems, and more particularly to a method and system for facilitating real time detection of linear infrastructural objects in aerial imagery. In one embodiment, a background suppression technique is applied to one or more hardware processors to a HSV image. Further, a mean shift filtering technique is applied to the hardware processors to find a peak of a confidence map and then a gradient image generation is performed for a plurality of edges of the image. A seed point pair along a middle cut portion of a linear feature of the HSV image to identify one or more boundaries of the seed point pair is extracted and then a contour growing approach to detect the boundaries of the linear feature is initiated. Lastly, one or more false positives are removed by using a rigidity feature, the rigidity feature being equivalent to the total sum of gradient orientations.

Abstract translation: 本公开一般涉及视觉检查系统，更具体地涉及一种用于促进航空图像中线性基础设施物体的实时检测的方法和系统。 在一个实施例中，将背景抑制技术应用于HSV图像的一个或多个硬件处理器。 此外，平均偏移滤波技术被应用于硬件处理器以找到置信图的峰值，然后对图像的多个边缘执行梯度图像生成。 提取沿着HSV图像的线性特征的中间切割部分的种子点对以识别种子点对的一个或多个边界，然后开始检测线性特征的边界的轮廓生长方法。 最后，通过使用刚度特征去除一个或多个假阳性，刚度特征等于梯度取向的总和。