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Driver’s Seat Belt Detection Using CNN

G Sai Lakshmi DS Bhupal Naik

2021Türk bilgisayar ve matematik eğitimi dergisi23 citationsDOIOpen Access PDF

Abstract

Seat belt detection is one of the necessary task which are required in transportation system to reduce accidents due to abrupt stop or high speed accident with other vehicles. In this paper, a technique is proposed to detect whether the driver wears seat belt or not by using convolution neural networks. Convolution Neural Network is nothing but deep Neural Network. ConvNet automatically collects features using filters or kernels from images without human involvement to classify the output images. Compared to different classification algorithms, preprocessing required in ConvNet is least. In this proposed method, first ConvNet is built and trained using Seatbelt dataset of both standard and non-standard. ConvNet learns the features from the images of seat belt dataset and performed better with an accuracy of 91.4% over SVM with 87.17% and an error rate of 8.55% when compared with SVM with 12.83% in case of standard dataset.

Topics & Concepts

Computer sciencePreprocessorSupport vector machineArtificial intelligenceConvolutional neural networkTask (project management)Artificial neural networkPattern recognition (psychology)Convolution (computer science)Seat beltWord error rateComputer visionEngineeringSystems engineeringAutomotive engineeringVehicle License Plate RecognitionAutonomous Vehicle Technology and SafetyIoT and GPS-based Vehicle Safety Systems
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