Abstract:
A method for vision machine inspection comprises providing depth information of a target acquired by an image capturing system, determining real-time three-dimensional information of a target object in a predetermined inspecting area based on depth information of at least one real-time image of the target. The method further comprises projecting color pixel information of a real-time color image of the target object to a three-dimensional virtual model based on the real-time three-dimensional information. The real-time color image may be acquired by a color camera system. The method further comprises generating a color three-dimensional virtual model. The color three-dimensional virtual model may comprise the color pixel information.
Abstract:
A calibration method applicable for an automation machining apparatus includes building a first stereoscopic characteristic model corresponding to an object, obtaining a stereoscopic image of the object, building a second stereoscopic characteristic model corresponding to the object based on the stereoscopic image, obtaining at least one error parameter corresponding to the second stereoscopic characteristic model by comparing the second stereoscopic characteristic model with the first stereoscopic characteristic model, and calibrating a machining parameter of the automation machining apparatus based on the at least one error parameter.
Abstract:
A method and an apparatus for reconstructing a three dimensional model of an object are provided. The method includes the following steps. A plurality of first depth images of an object are obtained. According to a linking information of the object, the first depth images are divided into a plurality of depth image groups. The linking information records location information corresponding to a plurality of substructures of the object. Each depth image group includes a plurality of second depth images, and the substructures correspond to the second depth images. According to the second depth image and the location information corresponding to each substructure, a local module of each substructure is built. According to the linking information, the local models corresponding to the substructures are merged, and the three-dimensional model of the object is built.
Abstract:
A method and an apparatus for reconstructing a three dimensional model of an object are provided. The method includes the following steps. A plurality of first depth images of an object are obtained. According to a linking information of the object, the first depth images are divided into a plurality of depth image groups. The linking information records location information corresponding to a plurality of substructures of the object. Each depth image group includes a plurality of second depth images, and the substructures correspond to the second depth images. According to the second depth image and the location information corresponding to each substructure, a local module of each substructure is built. According to the linking information, the local models corresponding to the substructures are merged, and the three-dimensional model of the object is built.
Abstract:
A machining parameter automatic generation system includes a geometric data capturing module, a feature recognition learning network and a machining parameter learning network. The geometric data capturing module captures a geometric shape of a workpiece to generate a candidate feature list. The feature recognition learning network trains the candidate feature list according to a first neural network model to obtain an applicable feature list. The machining parameter learning network trains the applicable feature list and the candidate machining parameter according to a second neural network model to obtain an applicable machining parameter. The applicable machining parameter is used to generate a machining program, and the machining program is read by a machine tool for processing.