The scanned text image is a non editable however it has the content yet one can't alter it or roll out any improvement, if required, to that filtered record. This gives a premise to the optical character acknowledgment (OCR) hypothesis. OCR is the way toward perceiving a sectioned part of the examined picture as a character. The general OCR comprises of three noteworthy sub forms like division, highlight extraction and afterward arrangement. Diverse acknowledgment models have been advanced as of late and distinctive research gatherings are taking a shot at the acknowledgment of Gurmukhi words. Division, Feature Extraction and arrangement are the pivotal periods of the character acknowledgment prepare that impact the general precision of the acknowledgment procedure. This paper will provide the overview of different techniques used for segmentation, feature extraction and classification of Gurmukhi scripts by different researchers and the conclusion obtained by them.
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