US 2020/0050922 A1 · RECYCLING SYSTEM AND METHOD BASED ON DEEP-LEARNING AND COMPUTER VISION TECHNOLOGY

Abstract

A recycling system and a method based on deep-learning and computer vision technology are disclosed. The system includes a trash sorting device and a trash sorting algorithm. The trash sorting device includes a trash arraying mechanism, trash sensors, a trash transfer mechanism and a controller. The trash arraying mechanism is configured to process trash in a batch manner. The controller drives the trash arraying mechanism according to the signals of trash sensors and controls the sorting gates of the trash sorting mechanism to rotate. The trash sorting algorithm makes use of the images of trash, wherein the images are taken by cameras in different directions. The trash sorting algorithm includes a dynamic object detection algorithm, an image pre-processing algorithm, an identification module and a voting and selecting algorithm. The identification module is based on the convolutional neural networks (CNNs) and may at least identify four kinds of trash.

Claims10

Dependent claims

A recycling system based on deep learning and computer vision technology, comprising:

a plurality of cameras, respectively configured to photograph a trash object in a plurality of directions and producing a plurality of trash object images;
a controller, connected to the plurality of cameras to receive the plurality of trash object images for identifying a type of the trash object, the controller comprising a data storage storing computer codes including:
a plurality of artificial neural network models, each trained by images taken in a direction corresponding to the plurality of directions, and identifying the trash object according to the plurality of trash object images to generate a judgment of the type of the trash object;
and
a voting and selecting algorithm, configured to combine the judgment of each artificial neural network model for generating a determination of the type of the trash object;
and
a trash sorting device, configured to receive the trash object and connected to and controlled by the controller;
wherein the trash sorting device delivers the trash object to a trash channel corresponding to the type of the trash object determined by the voting and selecting algorithm.

5 more elements

A computer implemented recycling method based on deep learning and computer vision technology for a trash sorting device, the recycling method comprising:

configuring a plurality of artificial neural network models in a controller, wherein each artificial neural network model is trained by images taken in a direction corresponding to a plurality of directions toward which a plurality of cameras are respectively configured;
configuring the cameras to photograph a trash object in the plurality of directions respectively and generate a plurality of trash object images;
connecting the plurality of cameras to the controller, and transmitting the plurality of trash object images to the controller;
identifying a type of the trash object as an identification result according to the plurality of trash object images through each artificial neural network model;
combining the identification results of the plurality of artificial neural network models and transmitting the identification results to a voting and selecting algorithm configured in the controller and connected to the plurality of artificial neural network models for generating a determination of the type of the trash object;
and
delivering the trash object to a trash channel corresponding to the determination of the voting and selecting algorithm through a trash sorting device connected to and controlled by the controller.

4 more elements

Dependencies are inferred from the claim text.

Recycling system and method based on deep-learning and computer vision technology

Life of this patent

Recycling system and method based on deep-learning and computer vision technology

Life of this patent

Abstract

Claims10