English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Image registration is the precondition of extracting document image content. A registration method for document image based on local feature image and Harris feature points detection is proposed. Firstly, a small amount of Harris feature points in the reference image are extracted so as to obtain the local feature image, then the Harris feature points of the registration image are also extracted, after that the feature points of the two images are matched by the Euclidean distance similarity measure and KD tree nearest neighbor searching. Secondly, in order to improve the accuracy and the efficiency of matching, the two-way maximum similarity matching is used to filtrate the matching point-pairs for the first time, and then RANSAC and the affine transformation are combined to complete the second filtrating and parameters estimation. Finally, the image is registered by using quadratic linear interpolation. The experimental results show that the proposed method has the high accuracy and efficiency of registration for the document image, and has a good resistance to image rotation, distortion and noise.

Document Image Registration Based on Local Feature Image and Harris Feature Points Detection