Ultra-fast basic geometrical transformations on linear image data structure

Vučković, Vladan; Arizanovic, Boban; Blond, Simon Le

doi:10.1016/j.eswa.2017.09.011

Cited by 3 publications

(1 citation statement)

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“…This paper presents further improvements of the authors" character segmentation approach, which forms part of a real time OCR system for the needs of the "Nikola Tesla Museum" in Belgrade [53][54][55][56]. This paper presents pre-processing methods for document image compression and decompression, which take place after the image binarization.…”

Section: Introductionmentioning

confidence: 99%

Efficient image compression and decompression algorithms for OCR systems

Arizanovic

Vučković

2018

FACTA U EE

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This paper presents an efficient new image compression and decompression methods for document images, intended for usage in the pre-processing stage of an OCR system designed for needs of the "Nikola Tesla Museum" in Belgrade. Proposed image compression methods exploit the Run-Length Encoding (RLE) algorithm and an algorithm based on document character contour extraction, while an iterative scanline fill algorithm is used for image decompression. Image compression and decompression methods are compared with JBIG2 and JPEG2000 image compression standards. Segmentation accuracy results for ground-truth documents are obtained in order to evaluate the proposed methods. Results show that the proposed methods outperform JBIG2 compression regarding the time complexity, providing up to 25 times lower processing time at the expense of worse compression ratio results, as well as JPEG2000 image compression standard, providing up to 4-fold improvement in compression ratio. Finally, time complexity results show that the presented methods are sufficiently fast for a real time character segmentation system.

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Section: Introductionmentioning

confidence: 99%