Utilizing a Two Planes Model to Rectify Documents With a Single Arbitrary Crease

Utilizing a Two Planes Model to Rectify Documents With a Single Arbitrary Crease

Blog Article

Document image rectification problem is crucial in document analysis.Most of the current state-of-the-art methods addressing it are data-driven and rely on neural network approaches.However, despite satisfactory rectifications, such methods’ time performance is poor, making them unsuitable for mobile on-device acquisition.

The present work concentrates on a specific (but common) rubbermaid 8 gallon trash can case of document physical distortion – the documents with a single crease.We investigate the properties of a surface comprised of two planes captured by a pinhole camera.Namely, we provide the methods to obtain the transformation between such an image and the template image having successfully localized the document in a frame.

It can be utilized in on-device recognition systems: it takes only 3 ms to estimate transformation parameters and about a quarter of a second to rectify an image on a smartphone CPU.We propose a novel dataset FDI-AC containing 200 real images of documents with a single crease in different positions.We conduct experiments comparing our approach with the current state-of-the-art setting a baseline performance on FDI-AC.

These experiments show that the jmannino.com proposed algorithm outperforms image rectification transformer network GeoTr in rectification accuracy and time performance.