• Ansari Rakhshi Fatma
• Namita Mishra
• Santosh K. Singh

Text Extraction plays a major role in finding vital and valuable information. Text extraction involves detection, localization, tracking, binarization, extraction, enhancement and recognition of the text from the given image. These text characters are difficult to be detected and recognized due to their deviation of size, font, style, orientation, alignment, contrast, complex colored, textured background. Due to rapid growth of available multimedia documents and growing requirement for information, identification, indexing and retrieval, many researches have been done on text extraction in images. Several techniques have been developed for extracting the text from an image. Text, which carries high-level semantic information, is a kind of important object that is useful for this task. When a machine generated text is printed against clean backgrounds, it can be converted to a computer readable form (ASCII) using current optical character recognition (OCR) technology. However, text is often printed against shaded or textured backgrounds or is embedded in images. Examples include maps, photographs, advertisements, videos, etc. Current document segmentation and recognition technologies cannot handle these situations well.

: Text Extraction, Image Text, Segmentation, OCR Technique, Document Text Images, Connected Components.

"Extraction of Text and Recognition of Images Using Segmentation & OCR in Matlab ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.949-953, June-2019, Available :http://www.jetir.org/papers/JETIR1906569.pdf

"Extraction of Text and Recognition of Images Using Segmentation & OCR in Matlab ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp949-953, June-2019, Available at : http://www.jetir.org/papers/JETIR1906569.pdf