发明名称 Image-based crack detection
摘要 Contact-less remote-sensing crack detection and/quantification methodologies are described, which are based on three-dimensional (3D) scene reconstruction, image processing, and pattern recognition. The systems and methodologies can utilize depth perception for detecting and/or quantifying cracks. These methodologies can provide the ability to analyze images captured from any distance and using any focal length or resolution. This adaptive feature may be especially useful for incorporation into mobile systems, such as unmanned aerial vehicles (UAV) or mobile autonomous or semi-autonomous robotic systems such as wheel-based or track-based radio controlled robots, as utilizing such structural inspection methods onto those mobile platforms may allow inaccessible regions to be properly inspected for cracks.
申请公布号 US8873837(B2) 申请公布日期 2014.10.28
申请号 US201213567943 申请日期 2012.08.06
申请人 University of Southern California 发明人 Jahanshahi Mohammad R.;Masri Sami F.
分类号 G06K9/62;G06T7/00;G06K9/00 主分类号 G06K9/62
代理机构 McDermott Will & Emery LLP 代理人 McDermott Will & Emery LLP
主权项 1. A system for crack detection, the system comprising: a storage device; and a processing system connected to the storage device; and a program stored in the storage device, wherein execution of the program by the processing system causes the system to perform functions, including functions that: (i) establish an appropriate structuring element based on a working distance and focal length of a three-dimensional (3D) structure of a scene; from a plurality of images of the scene;(ii) segment potential crack patterns by applying a morphological operation;(iii) determine appropriate features for each segmented pattern; and(iv) classify a crack from a non-crack pattern using a trained classifier, thereby forming a multiscale crack map,wherein: for the plurality of images of the scene there are a plurality of data acquisition parameters, wherein the relation between different image acquisition parameters is in accordance with the following:SF=(WDFL)⁢(SSSR)⁢n, where feature size (SF) is the size of a crack thickness represented by n pixels in an image, working distance (WD) is the working distance between camera and object, focal length (FL) is the camera focal length, sensor size (SS) (mm) is the camera sensor size, and sensor resolution (SR) is the camera sensor resolution in pixels; or the multiscale crack map is formulated in accordance with the following: and 0 otherwise; where Jm is the crack map at scale m of a structuring element, Smin, is the minimum structuring element size, Ck is the binary crack image obtained by using k as the structuring element, and u and v are the pixel coordinates of the crack map image.
地址 Los Angeles CA US