There are recently over 2 million people completely blind in Pakistan. Visually impaired person faces difficulty in limited movement and doing any work even in switching to operate any appliances. The blind people and those who are visually impaired are going through difficulties in recognizing thin
FACE RECOGNITION DETECTION SYSTEM FOR BLIND PEOPLE
There are recently over 2 million people completely blind in Pakistan. Visually impaired person faces difficulty in limited movement and doing any work even in switching to operate any appliances. The blind people and those who are visually impaired are going through difficulties in recognizing things in the surrounding environment. We aim to create an intelligent system , imitating the human eye, which transfers different scenes and images to the brain. The brain in turn analyses the images or scenes and based on previously stored information, the surrounding objects are identified. For this purpose, we use a small device that performs similar to the human brain, called "Raspberry Pi"; it is a small device that analyses the images and scenes with the help of the camera, which moves the images to the small device. Then, the process of analysis begins through Computer Vision Libraries. This Library analyses the images into parts to compare them with the most important characteristics of the objects in the images related to the database, through which the images are compared. When ensuring that the characteristics match the mathematical equations programmed in the language of Python, the objects in the image are detected. Finally, the sound of each tool in the database is called, and a message is sent to tell the blind about the tools in front of him.
Implemented tools and technologies that will be used in this project is a Raspberry Pi 4 Model B that acts as a processing unit, camera module for capturing images, micro-SD card for storage, headphones for sound output, power bank for portable power supply, Python as the programming language, Open CV for image processing libraries.
Our software aims to deliver a well-packed system that could be independently installed on a Raspberry Pi Module, inclusive of Raspbian OS. The software system is able to detect and recognize different people that are already fed into the database, along with the option to add more people through the system in real-time, those who aren’t fed into the system will be marked as strangers to the person who is using it. It will also be able to help the visually impaired or blind people to read books through the specially designed Optical Character Recognition (OCR) module that reads the text, and through the Text to Speech (TTS) engine it converts the text into audio for the user to listen to that audio and learn.
When a person approaches the blind person, his face image will be captured and compared to the list of faces on the database. If a match is found on the database, the system will announce the name of the person via speakers to the blind person.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry Pi 4 Model B (8 GB LPDDR4X) | Equipment | 1 | 15000 | 15000 |
| Camera module (Raspberry Pi High Quality Camera module) | Equipment | 1 | 15000 | 15000 |
| Ribbon cable for camera module 15 pin connector (3.3 Ft.) | Equipment | 1 | 2000 | 2000 |
| Ribbon cable for audio output module 40 pin connector | Equipment | 1 | 2000 | 2000 |
| Audio Output Module (IQaudIO DAC+) | Equipment | 1 | 8000 | 8000 |
| Speakers/headphones | Equipment | 1 | 3000 | 3000 |
| Power Bank | Equipment | 1 | 12000 | 12000 |
| Power Cable (USB C Type) | Equipment | 1 | 2000 | 2000 |
| Raspberry Pi 4 case (Black) | Equipment | 1 | 5000 | 5000 |
| Micro-SD card (64 GB): | Equipment | 2 | 2280 | 4560 |
| Micro-SD card (64 GB): | Miscellaneous | 2 | 2280 | 4560 |
| Total in (Rs) | 73120 |
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