Proposing an Applied, Simple, and Accurate Framework for the Image Processing Mission of Iran CanSat Competition

Janalipour, Milad; Abbaszadeh Tehrani, Nadia

doi:10.22034/jsst.2025.1548

Proposing an Applied, Simple, and Accurate Framework for the Image Processing Mission of Iran CanSat Competition

Document Type : Original Research Paper

Authors

Milad Janalipour ¹

Nadia Abbaszadeh Tehrani ²

¹ Aerospace Research Institute, Ministry of Science, Research and Technology, Tehran, Iran

² Aerospace Research Institute, Ministry of Science, Research, and Technology, Tehran, Iran

10.22034/jsst.2025.1548

Abstract

CanSat is an educational competition where students design miniature satellite systems integrated into soda-can-sized containers. Iran CanSat is a competition at the student level that is held each year. In the Remote Sensing-Communication class of the competition, an image processing mission is designed. Target detection and area estimation are the main missions of this competition. In this paper, a simple, applied, and accurate framework based on clustering algorithms is proposed to find targets and areas within them. K-means, fuzzy c-means, and genetic algorithm (GA) K-means algorithms are employed in this study. The proposed framework was applied to a simulated image and an image captured by a CanSat. Results show that the clustering algorithms are appropriate for detecting targets in the image. Experimental results demonstrated identical performance between K-means and GA-optimized K-means clustering, with both methods estimating target areas within 8 m² of ground-truth measurements. Notably, fuzzy c-means (FCM) clustering outperformed these approaches, achieving an accurate area estimation of 661.63 m² – closely approximating field measurements. This precision validates the proposed framework's efficacy for CanSat image processing missions, particularly in target detection and area quantification tasks under competition constraints.

Keywords

CanSat

Remote sensing

Image processing

K-means clustering

Genetic Algorithm

Subjects

Remote sensing

Article Title Persian

ارائه یک چارچوب دقیق، کاربردی و ساده برای ماموریت پردازش تصویر مسابقات کن ست ایران

Authors Persian

میلاد جانعلی پور ¹

نادیا عباس زاده تهرانی ²

¹ استادیار، پژوهشگاه هوافضا، وزارت علوم، تحقیقات و فناوری، تهران، ایران

² استادیار، پژوهشگاه هوافضا، وزارت علوم، تحقیقات و فناوری، تهران، ایران

Abstract Persian

مسابقه CanSat ایران، مسابقه‌ای در سطح دانشجویی است که هر ساله برگزار می‌شود. در بخش سنجش از دور این مسابقه، یک ماموریت پردازش تصویر طراحی می‌شود. در این مقاله، یک چارچوب ساده، کاربردی و دقیق مبتنی بر الگوریتم‌های خوشه‌بندی برای یافتن اهداف و نواحی درون آنها پیشنهاد شده است. الگوریتم‌های K-means، fuzzy cmeans و الگوریتم ژنتیک (GA) در این مطالعه به کار گرفته شده‌اند. چارچوب پیشنهادی بر روی یک تصویر شبیه‌سازی شده و یک تصویر گرفته شده توسط CanSat اعمال شد. نتایج نشان می‌دهد که الگوریتم‌های خوشه‌بندی برای تشخیص اهداف در تصویر مناسب هستند. علاوه بر این، مساحت تخمین زده شده توسط چارچوب پیشنهادی نزدیک به مساحت به دست آمده از اندازه‌گیری میدانی است.

Keywords Persian

کن ست

سنجش از دور

پردازش تصویر

خوشه بندی kmenas

الگوریتم ژنتیک

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