OCR can produce a substandard result if it has lower quality scanned image to process. Removal of non-essential elements is a way for gaining the better image for converting it from pictorial or scanned document to text using OCR for better result. A lot of factors like light and dark specks, skew, warp, and border artefacts play an important role in generating the best possible OCR results. Better the quality of the image, the better result you get. Scanned images always have some artefacts that affect the quality of the image, and pages are most times not aligned within the scanner which needs to be clipped to remove the border defects. Similarly, a skew of perspective warp needs to be corrected. The other common problem which downgrades the quality is noise in the document or image. It is an extra speck within the document either light or dark are most likely to occur when the document is scanned in black and white. Most OCR is performed upon binary images to enable faster analysis, transforming the scanned document to text data by scanning a document in a higher bit depth to improve the quality of the document by advanced image processing.