A Raspberry Pi Based Assistive Aid for Visually Impaired Users

According to who fact sheet of 2013, 39 million people are blind and 246 million have low vision. With 82% of blind population being 50 years old or above, there are many who have lived majority of their lives with an inability to do tasks like read, write or walk without help. This paper describes the implementation of Raspberry based assistive aid for visually impaired users using speeded up robust feature (SURF) algorithm. The proposed method develops a progressive work for developing an assistive aid for visually impaired, which will help them in colour identification, currency denomination recognition, obstacle detection as well as reading newspapers and books. The main advantage of using SURF method is its high speed and also ability to compare and recognize feature points of currency notes during payments. A prototype at the low cost is developed to the problems being faced by the visually impaired while interacting with their environment. Keyword : Raspberry pi, Speeded-up Robust Feature algorithm, Color Identification, Currency denomination, Low cost solution. INTRODUCTION : According to the most recent Investigations Report, two-thirds of all blind-persons are facing difficulty for their day-to-day navigation and other incidents. The visually impaired user generally uses a hand-held device with geo-magnetic effects that detects magnetic obstacles in their pathway during navigation. The system capable of localizing and reading aloud text embedded in natural scene images can be very helpful for blind and visually impaired persons providing information useful in everyday life, it increases their confidence and autonomy. Even though the currently available optical character recognition (OCR) programs are fast and accurate, most of them fail to recognize text embedded in natural scene images. The goal of the algorithm described in this paper is to localize text-like image regions and pre-process those in a way that will make OCR work more reliably. The approach described in the paper is based on colour image segmentation and segment shape analysis. Preliminary tests have shown that the proposed algorithm offers satisfactory detection rate and is pretty robust to typical text distortions, such as slant, tilt and bend. The multimodal neighbourhood signature (MNS) algorithm represents local object appearance by stable colourbased invariants efficiently computed from image neighbourhoods with multimodal colour density function. This paper is an effort to minimize the dependence of the user on the people around him while carrying out chores on a daily basis. The concept of a wearable device, which supports the general human tendency of pointing at objects to interact with the environment. Vol-3 Issue-2 2017 IJARIIE-ISSN(O)-2395-4396 4418 www.ijariie.com 2711 2. PROPOSED SYSTEM: For people who lost the optical ability to interpret their surroundings, way-finding that requires the person to navigate indoor or outdoor to the destination is often a daunting task. Recent advances in personal mobile devices capable of computing, communication and control, digital imaging, and global Positioning, which are widely available at affordable cost and offer potentials to enhance the global perception of the user’s Surrounds. However, these technologies are generally ineffective for uses by blind people, particularly in closerange navigation. Thus, Inspired by the ability of some biological organisms to detect geomagnetic(earth magnetic) fields as an orientation cue during migration or homing, this paper explores the use of geomagnetic field effects to extend the capability of personal devices to help blind people overcome some problems encountered in daily way-finding. In this project, four major issues are being addressed by the prototype. Initially, the inability to gauge the concept of colors of objects present around the user. The object colours are identifying using camera module. Then, the restrictions in identifying various currency notes while making payments. And fake currency can also be detected in this module. Lack of access to reading resources because of unavailability of reading material. Finally, Problem in avoiding obstacles present in path while walking indoors. In operation, the MTS communicates with a laptop PC through an inter-integrated circuit (I2C) bus and a USB adaptor, where the MTS output signals are filtered using 1-D median filter to remove noise.