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Active light source type object material identification system and method

An active light source and recognition system technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as complex operation, difficult to use, high measurement cost, etc., to reduce operation difficulty, reduce measurement cost, efficient and fast The effect of accurate classification

Pending Publication Date: 2021-06-08
李雯毓
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] The invention provides an active light source type object material identification system and method, which are used to solve the technical problems of the existing material identification scheme, which are complicated to operate, difficult to use, and require high measurement costs

Method used

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  • Active light source type object material identification system and method
  • Active light source type object material identification system and method

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Embodiment 1

[0047] Such as figure 1 As shown, the present invention discloses an active light source type object material identification system, including: an acquisition component and an identification component connected to the acquisition component, and the acquisition component is used to sequentially emit a variety of light rays with different spectral characteristics to be identified object, and collect multiple sets of reflection intensity data generated by the object to be identified reflecting a variety of different spectral characteristic light rays, and the multiple sets of reflection intensity data of the object to be identified correspond to a variety of different spectral characteristic light rays;

[0048] The identification component: used for comparing multiple sets of reflection intensity data of the object to be identified with multiple sets of reflection intensity data of different materials measured in advance, and judging the material of the object to be identified ac...

Embodiment 2

[0055] Embodiment 2 is a preferred embodiment of Embodiment 1. It differs from Embodiment 1 in that the structure and functions of the active light source type object material identification system are expanded, and the steps of the active light source type object material identification method are carried out. for refinement:

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Abstract

The invention discloses an active light source type object material identification system and method. A to-be-identified object is irradiated by sequentially emitting multiple light rays with different frequency spectrum characteristics; a plurality of groups of reflection intensity data generated when a to-be-identified object reflects the plurality of different frequency spectrum characteristic light rays is collected, wherein the plurality of groups of reflection intensity data of the to-be-identified object is in one-to-one correspondence with the plurality of different frequency spectrum characteristic light rays; and the multiple groups of reflection intensity data of the to-be-identified object are compared with multiple groups of reflection intensity data of different materials measured in advance, and the material of the to-be-identified object is judged according to the comparison result. Compared with an existing material identification scheme with simple illumination conditions and complex signal measurement, the operation difficulty of material identification can be reduced, and the measurement cost of material identification can be reduced.

Description

technical field [0001] The invention relates to the field of intelligent material identification, in particular to an active light source type object material identification system and method. Background technique [0002] Material recognition technology is a popular computer application research technology, which belongs to one of the research hotspots of computer vision. Especially in recent years, with the vigorous development of deep learning, deep learning has achieved great success in target detection and recognition. Using the method of deep learning to distinguish the type of material in the image through the CNN feature of the image is also a hot and difficult problem studied in recent years. Moreover, the recognition of materials is an important aspect of human perception of the surrounding environment, and it also plays a very important role in our lives. Different materials bring different perceptions to humans, such as leather products and textiles. It feels ve...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/78G06K9/20G06K9/00G06K9/62
CPCG06V20/10G06V10/141G06V10/143G06V10/10G06F18/2414
Inventor 李雯毓
Owner 李雯毓