9/25/2023 0 Comments Imagemagic convert set dpi![]() ![]() How to remove shadow from scanned images using OpenCVīy default Tesseract expects a page of text when it segments an image.page_dewarp - python example for Text page dewarping using a “cubic sheet” model.Details in blog Unprojecting text with ellipses. uproject text - python example how to recover perspective of image.Details in blog Compressing and enhancing hand-written notes. noteshrink - python example how to clean up scans.crop_morphology.py - Finding blocks of text in an image using Python, OpenCV and numpy.rotation_spacing.py - python script for automatic detection of rotation and line spacing of an image of text.Fred’s ImageMagick TEXTCLEANER - bash script for processing a scanned document of text to clean the text background.OpenCV - Rotation (Deskewing) - c++ example.If you need an example how to improve image quality programmatically, have a look at this examples: PRLib - Pre-Recognize Library with algorithms for improving OCR quality.OCR of movie subtitles) this can lead to problems, so users would need to remove the alpha channel (or pre-process the image by inverting image colors) by themself. Tesseract 4.00 removes the alpha channel with leptonica function pixRemoveAlpha(): it removes the alpha component by blending it with a white background. See for some details in tesseract user forum #427. If you OCR just text area without any border, tesseract could have problems with it. To address this rotate the page image so that the text lines are horizontal. The quality of Tesseract’s line segmentation reduces significantly if a page is too skewed, which severely impacts the quality of the OCR. Erosion can be used to shrink characters back to their normal glyph structure.įor example, GIMP’s Value Propagate filter can create Erosion of extra bold historical fonts by reducing the Lower threshold value.Ī skewed image is when a page has been scanned when not straight. ![]() Heavy ink bleeding from historical documents can be compensated for by using an Erosion technique. Many image processing programs allow Dilation and Erosion of edges of characters against a common background to dilate or grow in size (Dilation) or shrink (Erosion). Dilation and Erosionīold characters or Thin characters (especially those with Serifs) may impact the recognition of details and reduce recognition accuracy. Certain types of noise cannot be removed by Tesseract in the binarisation step, which can cause accuracy rates to drop. Noise is random variation of brightness or colour in an image, that can make the text of the image more difficult to read. See ImageJ Auto Threshold (java) or OpenCV Image Thresholding (python) or scikit-image Thresholding documentation (python). If you are not able to fix this by providing a better input image, you can try a different algorithm. Use tesseract -print-parameters | grep thresholding_ to see the relevant configurable parameters. Tesseract 5.0.0 added two new Leptonica based binarization methods: Adaptive Otsu and Sauvola. Tesseract does this internally (Otsu algorithm), but the result can be suboptimal, particularly if the page background is of uneven darkness. This is converting an image to black and white. “Willus Dotkom” made interesting test for Optimal image resolution with suggestion for optimal Height of capital letter in pixels. Tesseract works best on images which have a DPI of at least 300 dpi, so it may be beneficial to resize images. While tesseract version 3.05 (and older) handle inverted image (dark background and light text) without problem, for 4.x version use dark text on light background. If the resulting tessinput.tif file looks problematic, try some of these image processing operations before passing the image to Tesseract. You can see how Tesseract has processed the image by using the configuration variable tessedit_write_images to true (or using configfile get.images) when running Tesseract. It generally does a very good job of this, but there will inevitably be cases where it isn’t good enough, which can result in a significant reduction in accuracy. Tesseract does various image processing operations internally (using the Leptonica library) before doing the actual OCR. It’s important to note that, unless you’re using a very unusual font or a new language, retraining Tesseract is unlikely to help. There are a variety of reasons you might not get good quality output from Tesseract. Improving the quality of the output Tesseract documentation View on GitHub Improving the quality of the output Improving the quality of the output | tessdoc Skip to the content. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |