Image reconstruction and foreign matter detection method based on RPCA and PCA

A foreign object detection and image reconstruction technology, which is applied in image data processing, 2D image generation, character and pattern recognition, etc., to achieve the effect of less time consumption

Pending Publication Date: 2021-02-09
东莞市盟拓智能科技有限公司
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Problems solved by technology

[0030] The present invention is mainly to solve the detection problem of unknown defects in the MINILED industrial detection environment. The present invention can detect and locate most foreign objects under the premise of unknown defect details

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  • Image reconstruction and foreign matter detection method based on RPCA and PCA
  • Image reconstruction and foreign matter detection method based on RPCA and PCA
  • Image reconstruction and foreign matter detection method based on RPCA and PCA

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Embodiment Construction

[0054]In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. The drawings show preferred embodiments of the present invention. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive.

[0055]The present invention comprehensively utilizes the characteristics of the RPCA and PCA algorithms themselves, re-adjusts and optimizes, and designs the scheme of the present invention for image reconstruction and foreign object detection in MINILED application scenarios, which can meet the requirements of high precision and efficiency.

[0056]Such asfigure 1 As shown, this embodiment provides a single-channel basis vector acquisition process:

[0057](1) Single...

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Abstract

The invention relates to the technical field of defect detection, in particular to an image reconstruction and foreign matter detection method based on RPCA and PCA, and the method comprises the steps: obtaining a base vector: obtaining a sample image set; stretching and merging each sample image of the image set according to an RPCA algorithm; iterating a low-rank matrix large graph; performing standardization, downsampling and PCA decomposition to obtain a base vector and a transpose thereof required for converting the image data; reconstructing image data: performing matrix multiplication on the to-be-measured image and the base vector to obtain temporary data converted into a new space; carrying out matrix multiplication on the temporary data and the base vector transpose to obtain data converted back to the image space and subjected to noise reduction and foreign matter elimination; carrying out foreign matter detection: carrying out difference on the reconstructed image and a to-be-detected source image to obtain a set of noise data and foreign matter data; and screening noise out to obtain a foreign matter data set. According to the method, the RPCA algorithm and the PCA algorithm are combined for use, and the method can also take effect in a scene requiring real-time performance.

Description

Technical field[0001]The present invention relates to the technical field of defect detection, in particular to an image reconstruction and foreign object detection method based on RPCA and PCA.Background technique[0002]The current MINILED detection environment has objective reasons such as low pixel quality and too small original MINILED body, which cannot use traditional algorithms to detect and locate defects. At the same time, the industrial detection environment requires extremely high accuracy and detection efficiency.[0003]Currently, traditional algorithms include PCA and RPCA.[0004]PCA refers to the principal component analysis algorithm; principal component analysis is based on finding orthogonal bases to construct a new matrix numerical space, and convert the original numerical matrix to the new matrix numerical space to reduce the amount of data, thereby realizing data compression. It can eliminate special noise similar to Gaussian noise.[0005]Regarding PCA to find the or...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00G06K9/62
CPCG06T11/001G06F18/2135
Inventor 王海旭
Owner 东莞市盟拓智能科技有限公司
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