Automated Prototype for Asteroids Detection
This work addresses the challenge of asteroid detection for amateur astronomers and mini-surveys, but it appears incremental as it builds on existing software solutions and libraries.
The authors tackled the problem of detecting Near Earth Asteroids (NEAs) by proposing an automated pipeline prototype to replace manual detection methods like the blink technique, which becomes harder with larger CCD cameras, but no concrete results or numbers are provided.
Near Earth Asteroids (NEAs) are discovered daily, mainly by few major surveys, nevertheless many of them remain unobserved for years, even decades. Even so, there is room for new discoveries, including those submitted by smaller projects and amateur astronomers. Besides the well-known surveys that have their own automated system of asteroid detection, there are only a few software solutions designed to help amateurs and mini-surveys in NEAs discovery. Some of these obtain their results based on the blink method in which a set of reduced images are shown one after another and the astronomer has to visually detect real moving objects in a series of images. This technique becomes harder with the increase in size of the CCD cameras. Aiming to replace manual detection we propose an automated pipeline prototype for asteroids detection, written in Python under Linux, which calls some 3rd party astrophysics libraries.