Object Detection and Recognition for Visually Impaired People

Good vision is an expensive gift but now a day’s loss of vision is becoming common issue. Blind or visually impaired people does not have any conscious about the danger they are facing in their daily life. To help the blind people the visual world has to be transformed into the audio world with the potential to inform them about objects. Various challenges are faced by visually impaired patients even in the familiar environment. Visually impaired individuals are at drawback due to lack of sufficient information about their familiar environment. This project employs a Convolution Neural Network for recognition of pre-trained objects. This project employs in deep learning a deep Neural Network (DNN) for recognizing the object which is captured from the real world. The captured image is compared with some pre trained objects that is stored in dataset .The comparative of the object is based on the shape and size of an objects. In deep neural network, TensorFlow package using a model called Mobile Net SSD that is comparing the real time capture image with pre trained object based on shape, size of the object. If the image is matched with that trained object, it will display the name of the object. Then the name of the object is converted into audio output with the help of gTTS. This will helps to identify and detect what object is present in front of blind people and give output as audio.