Flash communication pattern analysis of fireflies based on computer vision

Abstract

Previous methods for detecting the flashing behavior of fireflies were using either a photomultiplier tube, a stopwatch, or videography. Limitations and problems are associated with these methods, i.e., errors in data collection and analysis, and it is time-consuming. This study aims to applied a computer vision approach to reduce the time of data collection and analysis as compared to the videography methods by illuminance calculation, time of flash occurrence, and optimize the position coordinate automatically and tracking each firefly individually. The Validation of the approach was performed by comparing the flashing data of male fireflies, Sclerotia aquatilis that was obtained from the analysis of the behavioral video. The pulse duration, flash interval, and flash patterns of S. aquatilis were similar to a reference study. The accuracy ratio of the tracking algorithm for tracking multiple fireflies was 0.94. The time consumption required to analyze the video decreased up to 96.82% and 76.91% when compared with videography and the stopwatch method, respectively. Therefore, this program could be employed as an alternative technique for the study of fireflies flashing behavior.

Species-Specific Flash Patterns Track the Nocturnal Behavior of Sympatric Taiwanese Fireflies

“…To process and analyze firefly flash signals, various imaging software have been or are being developed, such as TILIA [ 27 , 28 , 46 ]. Unlike other imaging software, FIJI / ImageJ is highly compatible with almost all computer operation systems and all video-imagery file formats [ 39 ].…”

“…In recent years, artificial intelligence (AI) on image pattern recognition has been intensively developed for various academic and industrial applications [ 47 , 48 ]. The use of AI in flash signal analysis and firefly species recognition is in development [ 27 ], and we anticipate that it will become a future trend. Until then, a complete digital database of firefly species-specific luminous features must be established.…”

“…Recently, improvements in photosensitivity and digital video recording technologies have allowed the luminous signaling to be recorded and stored as digital information. Hence, the spatiotemporal image analysis of flash patterns from a single individual or a population can be directly processed using a personal computer [ 27 , 28 ]. Flash patterns are thought to be a luminous marker for firefly species identification and classification, but this theory has only been investigated in a few species, such as members of the genus Photinus [ 13 , 14 ].…”