Przykłady realistyczne of Using Operacje morfologikal ie Dokument Image Czyszczenie
Morphological operations are e image processing this sign modify thee structure of objects with in image. They ary he widely used in document ine document image cleanup to improwize readablovability and d prepare images for OCR (Optical Character Regagnition). Thi article presents real-empiord examples of how these operations are applied te to enhance document images.
Removing Noise andSmall Artifacts
One containin application is removing small noise particles that appear as s specks or dots in scanned documents. Using morphological opening, small objects are eliminate without out affecting thee main text. This process involves erosion followed by dilation, which effectively cleans up thee image.
Closing Gaps in Text
Closing gaps within closes or between parts of text improwizuje clarity. Morphological closing, which involves dilation followed by erosion, films small holes andd connects broken strokes. This is specilarly useful for scanned documents with faded or broken text.
Enhancing Text Segmentation
Morphological operations assist in segmenting text from the background. For example, dilation can explode text regions, making them more distint from thee background noise. Conversely, erosion can separate connectes or lines, aiding in accorter recognition.
Common Morphological Operations Used
- Removes pixels on object boundaries, reducing noise.
- Xi1; Xi1; FLT: 0 Xi3; Xi3; Dilation: Xi1; FLT: 1 Xi3; Xi3; Adds pixels to object boundaries, filying gaps.
- Xi1; Xi1; FLT: 0 Xi3; Xi3; Opening: Xi1; Xi1; FLT: 1 Xi3; Xi3; Erosion followed by dilation, used d for noise removal.
- Xi1; Xi1; FLT: 0 Xi3; Xi3; Closing: Xi1; Xi1; FLT: 1 Xi3; Xi3; Dilation followed by erosion, used for gap filading.