Paper Title
Supervision Guidance for Visually Impaired using Machine Learning and Open CV Techniques

Abstract
Abstract - The electronic travel aid's primary function is to detect zebra crossings. It can find and estimate the direction of a zebra crossing, allowing the visually challenged to safely cross the road. In contrast to traditional approaches, a regression approach based on the RANSAC algorithm is used to identify zebra crossing. To detect the zebra crossing, the picture patches are loaded progressively into the logistic regression model. The zebra crossing picture patch is then given into the regression model, which predicts the direction. Before making predictions, the RANSAC algorithm optimises model parameters. The suggested technique may increase the precision recall performance of zebra crossing recognition and lower the root mean square error of anticipated directions when compared to existing methods.