Research on Digital Image Recognition Algorithm Based on Modular Intelligent Image Recognition

He, Xiaochen; Shao, Jingyi; Zhu, Jianguo

doi:10.1109/aeeca52519.2021.9574139

Cited by 1 publication

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“…This method can improve the recognition of information authenticity of data images, and is helpful to the development of data image information detection and recognition system based on improved fuzzy c-means clustering analysis. He et al [26] analyzes Canny algorithm, which uses Gaussian filter to smooth the image to eliminate the influence of noise on the detection results. Therefore, based on modular intelligent image recognition, four directions in 3 × 3 neighborhood are used to calculate gradient amplitude and direction.…”

Section: Introductionmentioning

confidence: 99%

Research on Digital Image Intelligent Recognition Method for Industrial Internet of Things Production Data Acquisition

He¹,

Li²

2022

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The real scene data of production images and videos collected by the perception layer of the industrial Internet of Things, which are shot under the conditions of lack of illumination, underexposure and insufficient contrast, need to be fully and efficiently utilized to ensure the smooth progress of the follow-up supervision, monitoring, detection and tracking of the industrial Internet of Things. Therefore, this paper studies the intelligent recognition method of digital images on production data collected by industrial Internet of Thing. Firstly, the video or image data collected by the industrial Internet of Things monitoring platform are preprocessed to achieve the purpose of image clarity and targeting. It includes constrained least square restoration and Lucy-Richardson restoration for image blur caused by defocus, and blind deconvolution restoration for image motion blur caused by vibration. The adaptive histogram equalization algorithm is described in detail, and it can enhance the global contrast of digital images collected by industrial Internet of Things while retaining the details of the target area as much as possible. Based on U-net convolution network, the target recognition model of digital images collected by industrial Internet of Things is constructed, and spatial convolution pooling pyramid and improved convolution module Inception are introduced to optimize the model. Experimental results verify the effectiveness of the model.

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Section: Introductionmentioning

confidence: 99%

Research on Digital Image Intelligent Recognition Method for Industrial Internet of Things Production Data Acquisition

He¹,

Li²

2022

View full text Add to dashboard Cite

show abstract

Research on Digital Image Recognition Algorithm Based on Modular Intelligent Image Recognition

Cited by 1 publication

References 10 publications

Research on Digital Image Intelligent Recognition Method for Industrial Internet of Things Production Data Acquisition

Research on Digital Image Intelligent Recognition Method for Industrial Internet of Things Production Data Acquisition

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