Safety helmet identification method integrating HOG human body target detection and SVM classifier

Abstract

The invention relates to the field of video monitoring, in particular to a safety helmet identification method integrating HOG human body target detection and an SVM classifier. The method includes the steps that parameter values Sigma of HOG positive and negative sample characteristics, an SVM classification function and a Gaussian kernel function are obtained; a monitoring box is extracted; a moving target is detected; HOG characteristic matching is conducted to judge whether a safety helmet is worn. By means of the safety helmet identification method, whether staff in a construction site wear safety helmets as required can be accurately monitored, the algorithm principle is simple, the real-time performance and a high accuracy rate are achieved, a human body target and a non-human-body target can be effectively distinguished, interference factors in a background are overcome, adaptability to outdoor changing light conditions and changes of colors of the safety helmets is achieved, and high robustness is achieved.

Description

technical field [0001] The invention relates to the field of video monitoring, in particular to a safety helmet identification method which combines HOG human target detection and SVM classifier. Background technique [0002] HOG (Histogram of Oriented Gradient): Histogram of Oriented Gradient is a feature descriptor used for object detection in computer vision and image processing. [0003] SVM (Support Vector Machine): Support Vector Machine is a trainable machine learning method. [0004] HSV (Hue, Saturation, Value): It is a color space created according to the intuitive characteristics of color. The parameters of the color in this model are: hue (H), saturation (S), and brightness (V). [0005] In the construction site, it is a very important requirement for the staff to wear safety helmets, which is directly related to the personal safety of the staff, so it is necessary to strictly monitor whether all the staff on the construction site wear safety helmets as required...

AI Technical Summary

Problems solved by technology

[0011] The purpose of the present invention is to provide a safety helmet recognition method that combines HOG human body target detection and SVM classifier, so as to solve the problem of insufficient monitoring accuracy and low accuracy in the prior art on whether the workers in the construction site wear safety helmets as required, and the monitoring Process and computationally complex problems

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