Garbage identification and classification method, computer readable storage medium and robot

A technology for identifying and sorting garbage, applied in the field of robotics, can solve problems such as low operating efficiency, poor feature matching effect, and missed detection of multiple frames, so as to improve detection speed and versatility, and reduce false detection rate and missed detection rate.

Pending Publication Date: 2022-04-26
广东盈峰智能环卫科技有限公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, because most of the garbage on the road has been squeezed and has different shapes, the feature matching effect is mostly poor.
In addition, due to the change of the viewing angle position during the movement of the robot, the

Method used

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  • Garbage identification and classification method, computer readable storage medium and robot
  • Garbage identification and classification method, computer readable storage medium and robot
  • Garbage identification and classification method, computer readable storage medium and robot

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Embodiment Construction

[0029] 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.

[0030] The garbage identification and classification method, computer-readable storage medium and robot proposed by the embodiments of the present invention are described below with reference to the accompanying drawings.

[0031] At present, the image detection algorithm based on deep learning can better detect the category and position of a specific target, and has a better detection effect on half-occluded objects. However, deep learning not only requires a large amount of image data for training, but also requires diversity i...

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Abstract

The invention discloses a garbage identification and classification method, a computer readable storage medium and a robot, and the method comprises the steps: carrying out the deblurring of an original frame image according to a preset deblurring network, and obtaining a target image; inputting the target image into a preset deep convolutional neural network model for target object detection to obtain a first feature vector diagram of the target object; and tracking the target object according to the first feature vector diagram, and sorting the target object according to the category and the position of the target object. According to the recognition method, the false detection rate and the omission ratio of ground garbage recognition can be effectively reduced, the detection speed and universality are improved, and the recognition method is less affected by the environment.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to a garbage identification and classification method, a computer-readable storage medium and a robot. Background technique [0002] In addition to cleaning fallen leaves, paper scraps and other debris during garbage inspection, traditional robots also need to detect, classify and collect recyclable garbage, so as to realize the recycling of recyclable garbage. When traditional algorithms detect recyclable garbage, they mostly segment the road surface in the image, and use algorithms such as connected domain detection, grayscale histogram, and feature matching to judge the category and location information of objects on the road surface, and then identify specific recyclable garbage. Garbage, such as plastic bottles, cans, etc., for recycling. However, because most of the garbage on the road has been squeezed and has different shapes, the feature matching effect is mostly poor. In ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08G06T7/246G06V10/764G06V10/774
CPCG06N3/084G06T7/246G06N3/045G06F18/241G06F18/214
Inventor 陈凯邓文轩张岁寒邵将张斌李伟超彭红霞简杰温礼刚
Owner 广东盈峰智能环卫科技有限公司
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