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Aliasing electronic component space expression method based on improved monocular depth estimation

A technology for electronic components and depth estimation, applied in computer components, neural learning methods, instruments, etc., to achieve the effect of solving aliasing electronic components, improving speed, and ensuring comprehensiveness

Pending Publication Date: 2021-10-01
JIANGSU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies in the prior art, the present invention provides a space expression method for aliasing electronic components based on improved monocular depth estimation, which can effectively solve the problem of autonomy in complex working scenarios where electronic components are aliased. identify problem

Method used

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  • Aliasing electronic component space expression method based on improved monocular depth estimation
  • Aliasing electronic component space expression method based on improved monocular depth estimation
  • Aliasing electronic component space expression method based on improved monocular depth estimation

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Embodiment Construction

[0031] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0032] Use the camera to collect images of different types of aliased electronic components in the material box to obtain RGB images of electronic components; each image is randomly scaled twice and cut randomly twice; using the lightweight algorithm in target detection and deep convolution algorithm to extract features from the processed image; fuse the extracted shallow features and deep features; after downsampling, fully connected layer, and classifier, the depth image, electronic component position information, and electronic...

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Abstract

The invention discloses an aliasing electronic component space expression method based on improved monocular depth estimation, which relates to the field of machine vision and comprises an image acquisition module, a target detection network module, a semantic segmentation network module and an HSV and RGB module. The image acquisition module is used for acquiring RGB images of different types of aliasing electronic components in the material box; the target detection network module is used for processing the RGB image acquired by the image acquisition module to obtain a depth image A; the semantic segmentation network module is used for segmenting the depth image A processed by the target detection network module to obtain rough depth information; and the HSV and RGB module is used for refining the rough depth information segmented by the semantic segmentation network module to obtain detailed depth information of each electronic component. According to the invention, the problem of autonomous identification of aliasing electronic components in a complex working scene can be effectively solved.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to a space expression method for aliasing electronic components based on improved monocular depth estimation. Background technique [0002] The autonomous recognition of electronic components is the basis of the visual control of intelligent assembly robots, and complex scene understanding is the basic support for the autonomous recognition of electronic components. Being able to accurately and autonomously identify electronic components is directly related to the accuracy and efficiency of intelligent assembly robot assembly. In actual production applications, the use of machine vision technology to assist manipulators in the assembly of electronic components not only solves the problems of low production efficiency, high labor input, and heavy burden on workers, but also fundamentally realizes the transition from traditional flow production to intelligent transformation of productio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08G06T7/10
CPCG06T7/10G06N3/08G06T2207/10024G06N3/045G06F18/241G06F18/253
Inventor 顾寄南雷文桐张可高伟
Owner JIANGSU UNIV
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