Portable Camera Based Visual Assistance for Blind People

The proposed system is a portable camera based visual assistance prototype for bind people to identify currency notes and also helps them to read printable texts from the handheld objects. To read printable texts, an efficient algorithm that combines an Optical Character Recognition (OCR) with Hierarchical optimization is used. In Pattern Recognition OCR every character is localized and separated then the resulting character image is sent to a pre-processor to reduce noise and to perform normalization. Certain characteristics will be extracted from the character for comparison. After comparison the identified characters are grouped and reconstructed to form original text strings, then the output is given to the speech engine to perform text to voice conversion. For identification of currency notes a novel recognition system is developed using SIFT (Scale Invariant Feature Transform) to improve precision and accuracy. The input image undergoes pre-processing and thereafter the distinct features are extracted and compared with the templates from the database. The resulting outcome is given through Earphone to the blind users.