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مه آبادی, امین اله. (1400). ردیابی بی درنگ همبندگرای اشیاء میکروسکوپی. پدافند الکترونیکی و سایبری, 9(3), 1-20.
امین اله مه آبادی. "ردیابی بی درنگ همبندگرای اشیاء میکروسکوپی". پدافند الکترونیکی و سایبری, 9, 3, 1400, 1-20.
مه آبادی, امین اله. (1400). 'ردیابی بی درنگ همبندگرای اشیاء میکروسکوپی', پدافند الکترونیکی و سایبری, 9(3), pp. 1-20.
مه آبادی, امین اله. ردیابی بی درنگ همبندگرای اشیاء میکروسکوپی. پدافند الکترونیکی و سایبری, 1400; 9(3): 1-20.

ردیابی بی درنگ همبندگرای اشیاء میکروسکوپی

پدافند الکترونیکی و سایبری
دوره 9، شماره 3 - شماره پیاپی 35، آذر 1400، صفحه 1-20    اصل مقاله (1.97 M)
نوع مقاله: مقاله پژوهشی
نویسنده
امین اله مه آبادی*
استادیار، دانشکده فنی مهندسی، دانشگاه شاهد، تهران، ایران
تاریخ دریافت: 20 شهریور 1399،  تاریخ بازنگری: 15 آبان 1399،  تاریخ پذیرش: 05 بهمن 1399 
چکیده
ردیابی تصویری اشیاء میکروسکوپی از مهم­ترین مطالعات­پویای فرآیندهای بیولوژیکی و نیازمند روش­های قطعه­بندی و ردیابی­خودکار است. اغلب محدود به­مورفولوژی اشیاء یا بررسی­ انسانیمی­شودو فاقد قدرت ­خودکارسازی ومقیاس­پذیریجهت تشخیص اشیاء،ردیابی­مسیر هر شیء وبررسیهمبندی آن­ها به­همراه تشخیص ناهنجاری­های مربوطهاست. این مقاله روشِسریعِ مقیاس­پذیرِ عامل­گرا برای تشخیصِ خودکار،ردیابیِبی­درنگویدیویی،ردیابی همزمان اشیاء میکروسکوپی، پایش رفتار هرشی و هم­بندی آن­ها براساس تئوری گراف قابل­کاربرددر اینترنت اشیاء ارایه می­کند که این محدودیت­ها را ندارد.روش قطعه­بندی آن ترکیبی از تغییرات زمانی و مکانی تصویر جهت تشخیص اشیاء متحرک و پیش‌بینی مسیر حرکت آن­ها است و امکان تشخیص ناهنجاری­ها­ی فردی شیءمانند مرگ­شی،توقف­شی متحرک، تصادم اشیاء، و خروج ناگهانی­از و ورود ناگهانی­به­ محدوده و ناهنجاری­های تغییرات­همبندیمانند تقسیم­­دسته­ها، تغییرات­دسته­، تجزیه­دسته، تغییرفاصله دسته­ها، میرایی­ و فروپاشی­شبکه را فراهم می­سازد. نتایج آزمایش‌های تجربی ردیابی­اشیاء میکروسکوپی اسپرم­ها و پرندگان در تصاویر دوبعدی از فضای سه­بعدی ویدیویی نشان می­دهد کهدارای حساسیت 99% و دقت 97% تشخیص بی­درنگ اشیاءبا دقت­ردیابی بالای 99% است. در پایش و ردیابی همبندی و تصادم اشیاء اسپرم دارای دقت 8/99%ودر پرندگان به­دلیل نویزهای محیطی و خطای­تشخیص در تغییرات سریع همبندی پرندگان دارای دقت 88% است.
کلیدواژه‌ها
اینترنت هرچیز؛ ردیابی بی درنگ همبندگرا؛ ردیابی اشیاء میکروسکوپی؛ تشخیص ناهنجاری؛ الگوریتم توزیعی؛ داده های عظیم؛ پردازش تصویر
عنوان مقاله [English]
Real-time Topology-based Tracking of Microscopic Objects
نویسندگان [English]
Aminollah Mahabadi
Assistant Professor, Faculty of Engineering, Shahed University, Tehran, Iran
چکیده [English]
Visual tracking of microscopic objects is one of the most important studies of dynamic biological processes and requires automated segmentation and tracking methods. It is often limited to the morphology of objects or human study and lacks the automation and scalability to detect objects, track the path of any object, and examine their topology with the detection of related anomalies. This paper presents a fast scalable agent-oriented method for automatic detection, real-time video tracking, simultaneous tracking of microscopic objects, monitoring object behavior, and their topology based on graph theory applicable to the Internet of Things. It has no mentioned restrictions. Its segmentation method is a combination of temporal and spatial changes of the image to detect moving objects and predict their movement path, and the possibility of detecting individual anomalies of the object (death, moving a stop, collision of objects, a sudden departure from and a sudden entry into processing frame). Provides abrupt onset and onset of anomalies (network splitting, batch changes, batch decomposition, batch spacing, attenuation, and network collapse). The results of experimental experiments to track microscopic objects of sperm and birds in 2D images of 3D video film show that it has 99% sensitivity and 97% accuracy of instantaneous detection of objects with 99% detection accuracy. In monitoring and tracking, correlation and collision of sperm objects have an accuracy of 99.8% and in birds due to environmental noise and error detection in rapid topology changes, birds have an accuracy of 88%.
کلیدواژه‌ها [English]
Real-time Topology-based Tracking, Microscopic Objects, Anomaly Detection, Image Processing, Distributed Algorithm, Internet of Things (IoT), Big Data
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