Abstract: A computing device and a method processes a point cloud of an object. The computing device constructs a curved surface according to the point cloud and triangulates the curved surface using a plurality of triangles. The computing device simulates each marked adjacent point and neighborhood points to a predetermined surface using a predetermined algorithm. The computing device projects each marked adjacent point onto a predetermined surface to obtain a projected point according to the type of the marked adjacent point.

Abstract: In a method for simplifying point clouds of an object using a computing device, a point cloud of the object is obtained from a scanning device connected to the computing device, and the point cloud is meshed into triangulated grids. The triangulated grids are selected from the point cloud, and a number of simplification passes to simplify the triangulated grids is received from an input device. The triangulated grids of triangles are classified according to a shape of each grid and a location of each grid in the point cloud. Each type of triangulated grid is simplified to obtain simplified grids by performing a loop triangular grid function with the number of simplification passes. The simplified grids are smoothed and the cloud model of the object can be displayed.

Abstract: A method for simplifying a mesh point cloud includes following steps: obtaining a point cloud and meshing the point cloud so that the point cloud is formed with a plurality of triangular grids; calculating a distance between a vertex of the triangular grid and its corresponding normal plane to determine an influence of the vertex to a geometric characteristic of the mesh point cloud; deleting the vertexes and the grids in connection therewith in accordance with a predetermined degree of simplification, wherein the deleted vertexes are those which have less influence to the geometric characteristic of the mesh point cloud; creating triangular grids to fill the void part in accordance with Delaunay triangulation; and smoothening the created grids.

Abstract: A computing device and a method detect a lightness of a lighting device. The computing device captures an image of the lighting device and parses the image to obtain a pixel gray value of each lighting dot of the lighting device. The computing device obtains detection information of the lighting device according to the pixel gray value of each lighting dot of the lighting device. The computing device generates a detection report of the lighting device according to the detection information of the lighting device.

Abstract: A computing device simulates a process of processing an object. The computing device calculates a moving space when a minimum bounding box of a model of a blade moves from a position point to an obtained path point. The computing device cuts a triangulated model of the object when the triangulated model of the object intersects the moving space.

Abstract: In a production accuracy verification method to verify a production program installed in a computer numerical control (CNC) machine, wherein the production program is used to produce a product, coordinates of points on an ideal processing path of the production program are obtained to fit a first curve. A CAD model of the product is obtained, and outlines of the product are extracted in the CAD model. A normal vector of each of the outlines is computed and to be adjusted, making the normal vectors of the outlines pointing to a same direction. First distances between points in the first curve and corresponding points in the second curve are computed, and whether the production program is accurate can be determined by comparing whether each of the first distances is within a first predetermined tolerance.

Abstract: A computing device compensates a coordinate of a position device for a computerized numerical control (CNC) machine. The computing device generates a point cloud according to contour points of the position device. The computing device deletes selected contour points from the point cloud upon the condition that the distance corresponding to each selected contour point exceeds a predetermined threshold. The computing device calculates an average coordinate of the contour points which are remained in the point cloud.

Abstract: A method for patching up a point cloud comprises obtaining a point cloud and a predetermined interval and a filtering parameter of curvature. Then a void in the point cloud which needs to be patched up is identified. A minimum encasing box is created to enclose the void. Points inside the minimum encasing box and outside the void are selected to create a B-spline curve surface. The B-spline curve surface are interpolated by the predetermined interval to obtain a plurality of discrete points which are used to patch up the void. Messy points in the void according to the predetermined interval and the filtering parameter of curvature are determined and deleted. Positions of the points in the void are adjusted along their normal vector directions to smooth the point cloud.

Abstract: Method of measuring a point cloud of an object includes obtaining the point cloud of the object from a storage device of the electronic device. Based on the point cloud, a triangular mesh surface is constructed and triangles of the triangular mesh surface are determined. According to the triangles, a reference plane is determined. According to the reference plane, a three dimensional (3D) object coordinate system is established. 3D object coordinates of points in the point cloud are calculated in the 3D object coordinate system. Measurement elements of a profile of the point cloud are determined and points in the point cloud corresponding to each of the measurement elements are determined. According to the 3D object coordinates of the determined points corresponding to each of the measurement elements, each of the measurement elements are fit. A distance and an angle of two fit measurement elements are calculated.

Abstract: A computing device and a method joins point cloud of an object. Two sets of initial corresponding points are obtained from two groups of point cloud. Abnormal points in the two sets of initial corresponding points are deleted to obtain two sets of remaining corresponding points. The method calculates an objective function and a least square solution of the two sets of remaining corresponding points and converts a first set of remaining corresponding points based on the least square solution. The converted first set of remaining correspondence points is joined with a second set of remaining correspondence points to form a group of joined point cloud when a precision of the objective function is within the preset precision value.

Abstract: A computing device and a method for patching point clouds of an object are provided. A point cloud of the object is acquired from a storage device of the computing device, and the point cloud is triangulated using several triangles. The method identifies a void in the point cloud to be patched, and obtains one or more triangles according to one or more included angles of neighboring sides of the void of the point cloud. The void of the point cloud is filled with the one or more obtained triangles. The filled triangles are adjusted according to normal vectors of the filled triangles, and the point cloud is rendered on the display screen.

Abstract: A method for processing a point cloud includes steps of obtaining the point cloud uploaded to an electronic device, creating a mesh point cloud made of a number of triangles from the point cloud, determining a primary reference triangle from the mesh point cloud, calculating a normal vector of the primary reference triangle, calculating a normal vector of the rest of the triangles, and adjusting a direction of the normal vector of corresponding one or more of the rest of the triangles that meet an adjusting condition. The adjusting condition is an included angle between a normal vector of an adjacent triangle and the normal vector of the primary reference triangle being greater than ninety degrees.

Abstract: An electronic device implementing a point cloud system is configured to simplify a mesh point cloud. The point cloud system obtains a mesh point cloud from a mesh cloud file uploaded to the electronic device, and obtains information of a number of triangles formed by the mesh point cloud. A unit normal vector of each vertex point of each triangle is calculated, and a decision value of each vertex point of each triangle is calculated. The vertex points of each triangle are classified into a number of classification levels according to the decision values. A number of sample vertex points from each of the classification levels is selected, and a triangular structure of the sample vertex points is restored to obtain a simplified mesh point cloud.

Abstract: A computing device and a method of processing point clouds of an object. Two groups of point clouds are jointed initially to form first jointed point clouds. An overlap area of the first jointed point clouds is identified and fitted to two curved surfaces. The method calculates initial correspondence points in the two groups of point clouds and obtains two sets of initial correspondence points. Abnormal points in two sets of initial correspondence points are deleted to obtain two sets of updated correspondence points. The method calculates a conversion relationship between the two groups of point clouds and calculates a least square solution corresponding to the conversion relationship. The method further converts one group of point clouds according to the conversion relationship, and joints the converted group of point clouds with another group of point clouds to be second jointed point clouds.

Abstract: A computing device and a method simulate a process of scanning a drawing of a three-dimensional (3D) object. The computing device triangulates a three-dimensional (3D) object using a plurality of 3D triangles. The computing device obtains converts the drawing of the 3D object into a drawing of a two-dimensional (2D) object. The computing device obtains 2D triangles from the drawing of the 2D object and displays the 2D triangles onto the drawing of the 3D object.

Abstract: A computing device and a method of processing point clouds of an object. Two groups of point clouds are selected as a first and a second group of point clouds. Redundant points in the first and second groups of point clouds are determined and marked using a first indicator. Normal points are determined in the second group of point clouds and marked using a second indicator. The method further uses a plurality of cubes for dividing the redundant points marked with the first indicator, and clears a first indicator of a specified redundant point in each of cubes which has a minimum distance to a centre point of the each of cubes. The method merges points which have not been marked with the first indicators in the first and second groups of point clouds to be a new group of point clouds.

Abstract: An electronic device having a processing unit and storage device receives point cloud data, and divides a bounding box of the point cloud data into a plurality of segmented boxes. Then, the processing unit selects a plurality of data boxes each having at least one point from the segmented boxes and assigns a reference value to each such point in the data boxes. The processing unit selects initial sampling points from the points in the data boxes, based on the reference values, to form a sample point cloud and adds to or subtracts from the sample point cloud based on the number of initial sampling points and a predetermined sampling rate.

Abstract: A method for reducing a point cloud includes receiving a mesh point cloud file uploaded to an electronic device and obtaining a number of data points of the point cloud from the mesh point cloud file, calculating a bounding box of the point cloud from the number of data points, dividing the bounding box into a number of cubes, determining effective cubes of the plurality of cubes, calculating a mean curvature of each of the effective cubes, determining a type of each of the effective cubes according to the mean curvature, reducing each effective cube according to the type of the effective cube to obtain a post-reduction cube, combining the post-reduction cubes to obtain a post-reduction point cloud, and restoring a mesh point cloud of the point cloud according to the post-reduction point cloud. An electronic device for reducing a point cloud is also provided.

Abstract: Framework for processing a point cloud of an object includes an electronic device coupled to a testing device. The testing device includes a worktable and a scanning device. The worktable has a number of labeled points. The electronic device controls the worktable to rotate at predetermined angles of rotation, and controls the scanning device to scan the worktable at each angle of rotation. A number of sets of points scanned by the scanning device is obtained. A transformation matrix of the sets of points is calculated according to coordinate positions of the labeled points of each set of points. A number of point cloud sets of an object placed on the worktable is obtained by scanning the object at corresponding angles of rotation. The point cloud sets are combined to obtain an overall point cloud according to the transformation matrix, and overlapping points of the overall point cloud are removed.

Abstract: In a method for outputting programs of a workpiece placed on a scanner device using a computing device, three-dimensional (3D) point cloud data of the workpiece is received from the scanner device. The received 3D point cloud data is meshed into a plurality of triangles, and a 3D model of the workpiece is obtained. A measurement point on the 3D model selected, and coordinates of the measurement point on the 3D model is calculated. A measurement element is created according to the calculated coordinates. A preset virtual probe is imported to be displayed on a display screen, and the virtual probe is rotated according to a normal vector of the created measurement element. The method controls the virtual probe to move towards the created measurement element, and outputs programs of the created measurement element.