Strip steel surface area type defect identification and classification method

Abstract

The invention discloses a strip steel surface area type defect identification and classification method which comprises the following steps: extracting strip steel surface pictures in a training sample database, removing useless backgrounds and keeping the category of the pictures to a corresponding label matrix; carrying out bilinear interpolation algorithm zooming on the pictures; carrying out color space normalization on images of the zoomed pictures by adopting a Gamma correction method; carrying out direction gradient histogram feature extraction on the corrected pictures; carrying out textural feature extraction on the corrected pictures by using a gray-level co-occurrence matrix; combining direction gradient histogram features and textural features to form a feature set, which comprises two main kinds of features, as a training database; training the feature data with an improved random forest classification algorithm; carrying out bilinear interpolation algorithm zooming, Gamma correction, direction gradient histogram feature extraction and textural feature extraction on the strip steel defect pictures to be identified in sequence; and then, inputting the feature data into an improved random forest classifier to finish identification.

Description

technical field [0001] The invention relates to the fields of machine vision, image processing, and pattern recognition, in particular to a method for identifying and classifying surface area defects of strip steel. Background technique [0002] Entering the 21st century, my country's manufacturing industry has entered an era of rapid development, which puts forward higher requirements for the quality and production capacity of basic raw materials. As one of the most important basic raw materials in the manufacturing industry, strip steel is indispensable in industrial manufacturing such as machinery, automobiles, ship hulls, and aviation. The importance of its output quality and production capacity to the country's economic development can be imagined. Manufacturers The product quality requirements for strip steel are getting higher and higher. The quality of strip steel products is controlled by many factors, mainly including the raw materials produced, rolling production...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies and defects mentioned in the background technology above, and to provide a strip surface area model that has the advantages of illumination, geometry and rotation invariance, and at the same time efficiently distinguishes the differences between complex defect features. Defect Identification and Classification Method

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