[IPOL announce] new article: Gestaltic Grouping of Line Segments

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2018/194/

Boshra Rajaei, and Rafael Grompone von Gioi,
Gestaltic Grouping of Line Segments,
Image Processing On Line, 8 (2018), pp. 37–50.
https://doi.org/10.5201/ipol.2018.194

Abstract
Using simple grouping rules in Gestalt theory, one may detect higher 
level features (geometric structures) in an image from elementary 
features. By recursive grouping of already detected geometric structures 
a bottom-up pyramid could be built that extracts increasingly complex 
geometric features from the input image. Taking advantage of the 
(recent) advances in reliable line segment detectors, in this paper, we 
propose three feature detectors along with their corresponding detailed 
algorithms that constitute one step up in this pyramid. For any digital 
image, our unsupervised algorithm computes three classic Gestalts from 
the set of predetected line segments: good continuations, non-local 
alignments, and bars. The methodology is based on a common stochastic a 
contrario model yielding three simple detection formulas, characterized 
by their number of false alarms. This detection algorithm is illustrated 
on several digital images.