An assistive text reading framework to help blind persons read text labels and product packaging from hand-held object in their daily resides is proposed. To isolate the object from cluttered backgrounds or other surroundings objects in the camera view, we propose an efficient and effective motion based method to define a region of interest (ROI) in the image of product. In the extracted ROI, text localization and recognition are conducted to acquire text information. To automatically localize the text regions from the object ROI, we propose a novel text localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Ada-boost model. Text characters in the localized text regions are then binarized and recognized by off-the shelf optical character recognition software. The recognized text codes are output to blind users in speech. Nowadays printed text appears everywhere like product names, restaurant menus, instructions on bottles, signed boards etc. Thus blind people need some assistance to read this text .This paper presents a camera-based product information reader to help blind persons to read information of the products. Camera acts as main vision in detecting the label image of the product then image is processed internally and separates label from image by using MATLAB and finally identifies the product name and identified product information is pronounced through the optical character recognition (OCR). The OCR is used to convert the text from text regions and then converted to voice output.