A Hybrid Approach for Identification of Manhole and Staircase to Assist Visually Challenged

Recognition of an object is a bare minimum restraint for an individual in order to sort out or classify the type of the object. This situation becomes a tricky experience with respect to the blind persons; therefore, to assist visually challenged persons, in particular, while recognizing the staircases and manholes, a prototype of mobility recognition is presented using the feature vector identification and sensor computed processor Arduino chips. This prototype provides more sovereignty to the sightless people while walking on the roads and helps to pass through on their own without any backing. This prototype is developed using Arduino kit along with feature detection module and helps the visually challenged in reaching their destinations with ease. A low weight stick is built to facilitate the visually challenged people toward effective recognition of the obstacles. In order to recognize the manholes, the chip is programmed and embedded in the stick that also holds the code for detection of the staircases based on a bivariate Gaussian mixture model; speeded up robust features algorithm is considered for extraction of features. The developed model shows an accuracy of around 90% for manhole detection and 88% for staircase detection.