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Part identification method based on multi-layer random forest

A random forest and recognition method technology, applied in the field of image processing, can solve problems such as increasing system flexibility

Pending Publication Date: 2019-12-06
QINGDAO TECHNOLOGICAL UNIVERSITY
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  • Abstract
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Problems solved by technology

In addition, in the modern automated assembly system, if the assembly robot can identify and monitor the assembly scene, it will greatly increase the flexibility of the system

Method used

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  • Part identification method based on multi-layer random forest
  • Part identification method based on multi-layer random forest
  • Part identification method based on multi-layer random forest

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Embodiment Construction

[0048] The present invention will be described in detail below in combination with specific embodiments.

[0049] The steps of the assembly state recognition and component recognition method of the present invention based on multi-layer random forest are as follows:

[0050] Step 1: Establishment of image training set and test set

[0051] Such as figure 1 As shown, the image sample set required for random forest classifier training is synthesized by computer three-dimensional graphics rendering. First, the CAD modeling software SolidWorks is used to establish a 3D model for the assembly to be recognized, and then it is imported into the visual modeling software Multigen Creator through the OBJ intermediate format and the assembly is marked with color. When constructing the assembly state training set, for each assembly state, use a different color to mark the assembly in this state; and when constructing the part training set in different assembly states, mark the assembly ...

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Abstract

The invention discloses a part identification method based on a multilayer random forest. The part identification method comprises the following steps: firstly, establishing an image training set anda test set; performing depth feature extraction; establishing a random forest classifier through training; and finally, constructing a multi-layer random forest for classification and identification.The beneficial effects of the invention are that the part identification method can achieve the recognition of the assembly state of the assembly and the recognition of parts at the same time, and canachieve the effective segmentation and recognition of the parts of the assembly in different assembly states.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a component recognition method based on a multi-layer random forest. Background technique [0002] With the development of augmented reality technology, the use of augmented reality technology for assembly induction has gradually attracted the attention of researchers from various countries. The application of augmented reality assembly guidance can improve the efficiency of manual manual assembly by fusing virtual guidance information with actual work scenarios in the operator's view. In order to obtain better human-computer interaction for augmented reality assembly guidance, it is necessary to identify and monitor the assembly scene. In addition, in the modern automated assembly system, if the assembly robot can identify and monitor the assembly scene, the flexibility of the system will be greatly increased. As for assembly scene recognition and monitoring, one of the...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/24323G06F18/214Y02P90/30
Inventor 李东年陈成军李昌明赵正旭郭阳
Owner QINGDAO TECHNOLOGICAL UNIVERSITY
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