Asteroids Detection Technique: Classic "Blink" An Automated Approch

Asteroids detection is a very important research field that received increased attention in the last couple of decades. Some major surveys have their own dedicated people, equipment and detection applications, so they are discovering Near Earth Asteroids (NEAs) daily. The interest in asteroids is not limited to those major surveys, it is shared by amateurs and mini-surveys too. A couple of them are using the few existent software solutions, most of which are developed by amateurs. The rest obtain their results in a visual manner: they “blink” a sequence of reduced images of the same field, taken at a specific time interval, and they try to detect a real moving object in the resulting animation. Such a technique becomes harder with the increase in size of the CCD cameras. Aiming to replace manual detection, we propose an automated “blink” technique for asteroids detection.

💡 Research Summary

The paper addresses the growing difficulty of manually detecting asteroids using the classic “blink” technique as CCD cameras become larger and image sequences longer. To automate this process, the authors present a modular pipeline that combines two Python‑based preprocessing modules with a Java‑implemented detection module called CrossObj. The preprocessing stage corrects raw CCD frames for bias, dark, flat‑field, and bad pixels, then applies field‑distortion correction using third‑party astrometry libraries to ensure accurate alignment of images taken with the 2.5 m Isaac Newton Telescope’s Wide Field Camera (four 2k × 4k CCDs, 0.33″ pixel⁻¹). After reduction, SExtractor generates source catalogs containing each object’s full‑width‑half‑maximum (FWHM), right ascension, declination, and magnitude.

CrossObj selects the image with the smallest median FWHM as a “pivot” because it represents the best seeing conditions. Fixed celestial sources (stars, galaxies) are removed by matching catalog entries across frames using a spherical distance formula:
d = arccos