Visual capture method and device based on depth image and readable storage medium
A deep image and vision technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as misjudgment and affect the accuracy of object recognition, save storage space, reduce program running time, and improve robustness sexual effect
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2018-03-02
- Estimated Expiration
- Not applicable · inactive patent
Smart Images

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Abstract
Description
technical field
[0001] The present invention relates to the field of robot visual grasping, in particular to a depth image-based visual grasping method, device and readable storage medium. Background technique
[0002] Robot visual grasping is one of the very important research directions in the field of robot research. This importance is mainly reflected in its wide range of application scenarios. Not only in the factory assembly line, it is necessary to use a large number of mechanical arm visual grasping to complete the assembly work. Moreover, in daily service robots, robotic arm vision grasping is also required to complete daily work. More importantly, with the rise of online shopping and the Internet of Things, it is becoming increasingly important to intelligently classify and select items in warehouses. At the same time, robotic arm vision Grasping also involves a multidisciplinary approach, including disciplines such as automatic control science, image processing, m...
Examples
Embodiment Construction
[0037] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0038] see figure 1 , an embodiment of the present invention provides a visual capture method based on a depth image, comprising the following steps:
[0039] Step 100: Obtain the point cloud image, and segment the obtained point cloud image through the RANSAN random sampling consensus algorithm and the Euclidean clustering algorithm, and segment the target object to be identified.
[0040] see figure 2 First, the point cloud image 101 of each object is acquired through the depth camera Kinect, and the point cloud image includes position information (x, y, z) and color information (R, G, B) of the object. Before segmenting the target object from the point cloud image acquired by the depth camera Kinect, filter the point cloud image information far from the targ...