Menu Close

What kind of preprocessing is needed for OCR?

What kind of preprocessing is needed for OCR?

The sample image below clearly needs some preprocessing like binarization, deskewing and removal of scanning artefacts. Ensure that the images are scaled to the right size which usually is of at least 300 DPI (Dots Per Inch).

What does it mean when no text is recognized by OCR?

The empty results.Text indicates that no text is recognized. In the keypad image, the text is sparse and located on an irregular background. In this case, the heuristics used for document layout analysis within ocr might be failing to find blocks of text within the image, and, as a result, text recognition fails.

How is Optical Character Recognition ( OCR ) used?

Optical Character Recognition (OCR): Image alignment (often called document alignment in the context of OCR) can be used to build automatic form, invoice, or receipt scanners. We first align the input image to a template of the document we want to scan.

When to use a uniform background for OCR?

These kind of OCR errors can be identified using the confidence values before any further processing takes place. ocr performs best when the text is located on a uniform background and is formatted like a document. When the text appears on a non-uniform background, additional pre-processing steps are required to get the best OCR results.

The sample image below clearly needs some preprocessing like binarization, deskewing and removal of scanning artefacts. Ensure that the images are scaled to the right size which usually is of at least 300 DPI (Dots Per Inch).

How to improve the accuracy of OCR engine?

Use the following image processing operation to improve the quality of your input image. Image Rescaling is important for image analysis. Mostly OCR engine give an accurate output of the image which has 300 DPI.

How does DPI affect the accuracy of OCR?

DPI describes the resolution of the image or in other words, it denotes printed dots per inch. A Skewed image is defined as a document image which is not straight. Skewed images directly impact the line segmentation of OCR engine which reduces its accuracy. We need to process the following steps to correct text skew.

How to OCR A document with TesseracT, OpenCV, Python?

Figure 5: Presenting an image (such as a document scan or smartphone photo of a document on a desk) to our OCR pipeline is Step #2 in our automated OCR system based on OpenCV, Tesseract, and Python. We can then ( Step #3) apply automatic image alignment/registration to align the input image with the template form ( Figure 6 ).