Real Time Indoor Object Detection Aid for Blind (original) (raw)

Real Time Object Detection for Visually Impaired Person

According to statistics from the World Health Organization (WHO), at least 285 million people are visually impaired or blindness. Blind people generally have to rely on white canes, guide dogs, screen-reading software, magnifiers, and glasses for navigation and surrounding object detection. Therefore, to help blind people, the visual world has to be transformed into the audio world with the potential to inform them about objects. In this paper, we propose a real-time object detection system to help visually impaired people in their daily life. This system consists of a Raspberry Pi in which YOLO (You Only Look Once) deep learning algorithm is employed. We will use YOLOv3 real-time Object Detection algorithm trained on the COCO dataset to identify the object present before the person. Then the label of the object is identified and then converted into audio by using Google Text to Speech (gTTS), which will be the expected output.

Object Detection System with Voice Alert for Blind

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023

As we can see, there are numerous blind persons nearby who encounter various challenges, such as difficulty in crossing roads and identifying objects in their environment. With the advancement in technology in several fields, human life is evolving to better standards. Unfortunately, those who are blind are unable to fully enjoy this kind of lifestyle. So, this project is one strategy for introducing blind individuals to a new way of living that makes them independent on others. The major goal of this project is to create a deep-learning algorithm that can be used to analyse the environment for people who are blind by using the rapidly evolving technology. We'll accomplish this using object detection and transform the data into speech alerts and warnings. Real-time object detection is one of the more challenging tasks since it requires continuous processing and takes a long time. The convolution neural network is the main backbone for any type of object detection (CNN). We can create algorithms based on photos and videos by employing a convolution neural network. We utilise the YOLO technique for object detection because it is simple and quick to process. In addition, for the voice warnings, we employed Text to Speech (TTS). The dataset used in this technique is the COCO dataset, which contains the names of things and objects in our daily lives. These algorithms have been thoroughly trained by the over 90 outdoor objects that we view every day in our daily lives.

Voice Enable Blind Assistance System -Real time Object Detection

IRJET, 2022

Real-time object detection is a difficult operation since it requires more computing power to recognise the object in real time. However, the data created by any real-time system is unlabeled, and effective training frequently necessitates a huge quantity of labelled data. Single Shot Multi-Box Detection is a quicker detection approach for realtime object detection, based on a convolution neural network model proposed in this paper (SSD). The feature resampling stage was eliminated in this work, and all calculated results were merged into a single component. Still, a lightweight network model is required for places with limited processing capability, such as mobile devices (eg: laptop, mobile phones, etc). In this suggested study, a lightweight network model called MobileNet is adopted, which uses depth-wise separable convolution. The usage of MobileNet in conjunction with the SSD model increases the accuracy level in detecting real-time household objects, according to the results of the experiments.

Blind Person Assistant: Object Detection

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

It's a known fact that estimated number of blind persons in the world is about 285 million, approximately equal to the 20% of the Indian Population. They are mostly dependent on someone for even accessing their basic daily needs. In our project, we used TensorFlow, it's a new library from Google. TensorFlow model our neural networks. The TensorFlow Object Detection API is used to detect many objects. We have Introduce an algorithm (SSD). SSD uses a similar phase while training, to match the appropriate anchor box with the bounding boxes of each ground truth object within an image. Essentially, the anchor box with the highest degree of flap with an object is responsible for predicting that object's class and its location. It has microcontroller which has wi-fi inbuilt module. This guide is convenient and offers data to the client to move around in new condition, regardless of whether indoor or open air, through an ease to use interface. Then again, and so as to lessen route challenges of the visually impaired, a deterrent location framework utilizing ultrasounds is added to this gadget. The proposed framework identifies the closest hindrance through ultrasonic sensors and it gives an alert to illuminate the visually impaired about its confinement.

Development of a Smart Device for Blind & Visually Impaired Person using Computer Vision

2018

Developing a tool for the visually impaired people is a trivial area of concern. However, use of computer vision in these devices is a fairly new trend and recent topic of interest. There are several works using computer vision techniques which focus on specific requirements of blind people. But there is no existing methods that help to solve all the basic needs of blind person. In this paper, we propose an idea of a device which can capture images in real time and comprehend its equivalent speech directly into the ear of visually impaired person. This new system may solve some of major problems of blind persons that are still exists. The prototype facilitates object detection using image recognition techniques. Open Computer Vision (OpenCV) performs image analysis, classification of images and prediction of the type of object on household object dataset. This prediction is converted to audio output using gTTS (Google Text to Speech Converter). This audio output can be fed to earpho...

Sanjaya: A Blind Assistance System

IRJET, 2022

According to the World Health Organization (WHO), there are approximately 284 million people worldwide who have limited vision, and approximately 39 million who are completely blind [10]. Visually impaired people confront multiple challenges in their daily lives, particularly when navigating from one place to another on their own. They frequently rely on others to meet their daily needs. The proposed system is intended to help the visually impaired by identifying and classifying common everyday objects in realtime. This system provides voice feedback for improved comprehension and navigation. In addition, we have depth estimation, which calculates the safe distance between the object and the person, allowing them to be more self-sufficient and less reliant on others. We were able to create this model using TensorFlow and pre-trained models. The recommended strategy is dependable, affordable, realistic, and feasible.

A Smart Assistance for Visually Impaired

IRJET, 2023

Independent living is one of the major concerns for people around the globe. But when it comes to people who are visually challenged, they always rely on other people to get their daily things done. In today's advanced technical environment, the need for self-sufficiency is recognized in the situation of visually impaired people who are socially restricted. More than 90% of individuals with blindness and low vision are mostly seen in developing countries. Visually impaired people always need the help of others, and they rely on others for essential needs. In this project, we developed a system that uses a conglomeration of technologies like Object detection, Speech Recognition, etc, to solve the problems faced by blind people to a certain extent. It makes use of a camera module that acts as a virtual eye for the visually impaired and helps them recognize objects surrounding them. This system also includes other features like searching Wikipedia and sending emails. All the features are implemented using a headset that provides voice assistance for an easier lifestyle for the visually impaired. The whole system was developed in the Python programming language.

Proposed System on Object Detection for Visually Impaired People

2018

Walking safely and confidently without any human assistance in urban or unknown environments is a difficult task for blind people. Blind people face several problems in their life, one of these issues that is the most vital one is identification the hindrances when they are walking. When moving from one place to another, they need help of other people around. Their independency in strolling is lost. Sticks can be usable but are not that reliable nor does everyone have it. A visually impaired person needs absolution to help him overcome problems in navigation due to his disability. The project is mainly focused on providing a type of visual aid to the visually impaired people. With the current advances in comprehensive innovation, it is conceivable to stretch out the help given to individuals with visual hindrance during their mobility. In this context we propose system in which an Android smartphone is used to help a blind user in obstacle detection and navigation. Today, smartphone...

Detection of Object Scene and Motion in a Smartphone Application for Visually Impaired Users

In this work we describe main features of software modules developed for android smart phone that are dedicated for the blind user or visually impaired user. To detect the object by using smart phone store the name of that object and at the time when user want to search object smart phone convert the name of object into speech and tell blind user. We use ANN(Artificial Neural Network) for detecting the object we also detect the whole scene such as college, house instead of single object and also the any movement happen in front of camera that is motion detection.

Real-Time Object Detection and Recognition System for the Visually Impaired

Journal of Real-Time Object Detection and Recognition System for the Visually Impaired, 2024

This paper presents a real-time object detection and recognition system aimed at assisting visually impaired individuals in navigating their surroundings. The system leverages machine learning and computer vision technologies, specifically using the COCO-SSD model, to identify and classify objects from a live video feed. Audio feedback informs the user of detected objects in real time, enhancing mobility and independence. This solution is compatible with modern devices equipped with a camera and has the potential for further development with advanced object recognition models and user interaction features.