Synthetic Edges for Corner Training DATA

Published: 10 January 2019| Version 2 | DOI: 10.17632/pr246v6594.2
Contributor:
Jean Diaz

Description

The training dataset is composed by 31x31pixels images of synthetic edges of 38160 (73.6%) CORNERS and 13680 (26.4%) NO-CORNERS. We generated, from the central pixel, two line segments, L1 and L2, that are oriented by the angles a1 and a2 respectively as shown in "line-segments.png". The angles vary from 0° to 355°, in increments of 5°. When the inner angle between L1 and L2 is less than 140°, the descriptor that is associated to the central pixel belongs to the CORNER Class. Otherwise, a greater angle is considered a straight line and the central pixel belongs to the NO-CORNER class. Aiming to obtain a noise-robust corner detector, we generated ten images with salt and pepper noise with 0.04 as noise density, for each combination (L1,L2) as shown in "dataset.png".

Files

Categories

Computer Vision, Computational Pattern Recognition, Image Processing, Corner Detection

Licence