For blind persons it is very essential to recognize a product of their daily use so we implied a method to identify product in their everyday routine by use of camera. To separate an object from un-necessary background, movement-based technique is used to spot object of concern from the camera by instructing person about recognized objects. 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 it’s quite complicated and it’s a difficult task. Object detection is used in many scenarios. Conventional methods of these object detection depend on huge number of datasets and it also takes large amount of time to train these data. Training of small or unseen objects is a more challenging task. Human brains and visual systems are more accurate and faster in detecting objects in real time and has conscious thoughts in detecting obstacles. Due to the availability of large amount of data and with more advanced technologies and better working algorithms, classification and detection of multiple objects in the same frame has become easy with high accuracy. The main objective of the project is to design and implement a real time object recognition using real time camera with navigation system. And also using implement text detection and recognition system to extract the text from captured image using Optical character recognition algorithm. We can implement the system in real time environment using Python as front end.