Kıyı bölgelerindeki denizanası yoğunluğunun İHA görüntülerinden gerçek zamanlı tespiti için kavramsal bir sistem önerisi

Year 2023, Volume: 39 Issue: 2, 192 - 203, 31.08.2023

Serkan Dereli , Mehmet Okuyar , Emin Güney

Abstract

Bu çalışmada, küresel ısınmaya bağlı olarak kıyı bölgelerinde meydana gelen denizanası istilasından erken haberdar olmak ve gerekli önlemleri almak amacıyla insansız hava araçlarında kullanılabilecek bir sistem önerilmiştir. Bu araştırmadaki asıl mesele, insansız sistemlerin izleme ve bilgi toplama alanındaki maharetinin denizanası istilalarını tespit etmek için kullanılmasıdır. Bunun için önerilen yöntem, görüntü işlemede üst üste binen, kısmen gizlenen veya tüm ayrıntıların açıkça görülemediği nesneleri başarıyla oluşturabilen havza algoritmasından başka bir şey değildir. Alanda yapılan araştırmalar, testler ve uygulamalar bunun için iki önemli koşulun oluşması gerektiğini ortaya koymaktadır. Bunlardan ilki denizanasının yoğunluğunun doğru olarak elde edilmesi, diğeri ise işlemin İHA sisteminde gerçek zamanlı olarak gerçekleştirilmesidir. Bu amaçla önerilen sistem ilk olarak CPU tabanlı bir bilgisayarda test edilip doğrulanmış, ardından aynı kodun GPU tabanlı gömülü bir sisteme taşınma süreci analiz edilmiştir. Son aşamada CPU ve GPU ile elde edilen veriler karşılaştırıldığında, önerilen yöntemin bir İHA sisteminde rahatlıkla kullanılabileceği ve iklim değişikliğinin neden olduğu deniz ekosisteminin izlenmesinde başarılı sonuçlar vereceği açıktır.

Keywords

Havza algoritması, Deniz anası tespiti, bilgisayarlı görme, gömülü sistemler, uçta hesaplama

A conceptual system proposal for real-time detection of jellyfish density in coastal areas from UAV images

Abstract

In this study, a system that can be used in unmanned aerial vehicles is proposed in order to be informed early about the jellyfish infestation in coastal areas due to global warming and to take necessary precautions. The main thing in this research is that the dexterity of unmanned systems in the field of monitoring and information gathering was used to detect jellyfish infestations. The proposed method for this is nothing but the watershed algorithm, which can successfully create objects that are overlapped, partially hidden or not all details are clearly visible in image processing. Researches, tests and applications in the field reveal that two important conditions must occur for this. The first of these is to obtain the density of jellyfish correctly, and the other is to perform the process in real time in the UAV system. For this purpose, the proposed system was first tested and verified on a CPU-based computer, and then the process of moving the same code to a GPU-based embedded system was analyzed. When the data obtained with the CPU and GPU are compared at the last stage, it is obvious that the proposed method will be used easily in a UAV system and will yield successful results in monitoring the marine ecosystem caused by climate change.

Keywords

watershed algorithm, jellyfish detection, computer vision, embedded systems, edge computing

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