CCTV TASVIRLARIGA RAQAMLI ISHLOV BERISH VOSITALARI, ALGORITMLAR VA MODELLARINING QIYOSIY TAHLILI

Jamshid Hamzayev

Mualliflar

Jamshid Hamzayev Muallif

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CCTV, raqamli tasvirlarga ishlov berish, obyektlarni aniqlash, Gauss filtri, Sobel operatori, Canny edge detection, Haar cascade, YOLO, Optical Flow, Background Subtraction, Deep Learning, CNN, Median filter, Bilateral filter, Gabor filter.

Abstrak

Ushbu maqola CCTV tasvirlariga raqamli ishlov berish sohasidagi keng qamrovli tadqiqotni taqdim etadi. Unda avvalo tasvirlarni oldindan qayta ishlash (noise reduction, filtering), chegara va xususiyatlarni ajratish (edge detection, feature extraction), obyektlarni aniqlash va lokalizatsiya (classical va chuqur modellar), hamda harakatni kuzatish va fonni ajratish (motion analysis, background modelling) kabi bosqichlar bo‘yicha eng ko‘p ishlatiladigan algoritmlar va modellarning matematik asoslari hamda amaliy xususiyatlari batafsil tahlil qilingan. Har bir usulning ishlash printsipi (masalan, Gauss yadrosi bilan konvolyutsiya, Sobel va Canny uchun gradient va non-maximum suppression, YOLO va CNN uchun konvolyutsion qatlamlar va bounding box regressiyasi), afzalliklari (tezlik, aniqlik, real vaqtda ishlash qobiliyati) hamda kamchiliklari (shovqin sezgirligi, hisoblash resurslari talabi, kichik obyektlarni aniqlashdagi muammolar) qiyosiy ravishda taqdim etilgan.

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Bibliografik havolalar

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