ABSTRACT The goal of the present project is to model an object detector to detect objects for visually impaired people and other commercial purposes by recognizing the objects at a particular distance. Available old techniques for object detection needed large training data it takes more time and its quite complicated and it’s a difficult task. Hence, in this paper, we propose computer vision concept to convert object to text by importing the pre trained dataset model from the caffemodel framework and the texts are further converted into speech. This system supports multiple object detections on a single screen, that is it helps in real time object detection. This paper involves the idea and methodology and system architecture to implement the system along with the obtained intermediate results and performance analysis of the tools used in the proposed system. This system can further be implemented in any portable devices for the visually impaired people to detect objects at a particular distance from them.