Text Information Extraction And Analysis From Images Using Digital Image Processing Techniques

Text data present in images contain useful information for automatic explanation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging in the computer vision research area. The proposed methods compare two basic approaches for extracting text region in images: edge-based and connected-component based. The algorithms are implemented and evaluated using a set of images that vary along the dimensions of lighting, scale and orientation. Accuracy, precision and recall rates for each approach are analyzed to determine the success and limitations of each approach.