Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Thuật toán RANSAC thích ứng và mở rộng cho nhận diện đối tượng trong các hình ảnh viễn thám
Tóm tắt
Trong bài báo này, một phương pháp mới được đề xuất cho việc nhận diện đối tượng trong các hình ảnh viễn thám. Trong phương pháp được đề xuất, quá trình khớp giữa đối tượng trong hình mẫu và hình ảnh thử nghiệm được thực hiện dựa trên Biến đổi Đặc trưng Không nhạy với Tỷ lệ (SIFT). Để giảm thiểu các khớp sai của SIFT, một thuật toán đồng thuận mẫu ngẫu nhiên thích ứng (RANSAC) được sử dụng. Trong RANSAC được đề xuất, giá trị ngưỡng được tính toán một cách thích ứng dựa trên trung bình và phương sai của các điểm khớp đúng và sai. Cuối cùng, ranh giới chính xác của đối tượng được trích xuất bằng cách sử dụng thuật toán tăng trưởng vùng mở rộng. Thuật toán được đề xuất sử dụng các điểm khớp đúng như nhiều điểm gốc thay vì một điểm gốc duy nhất. Phương pháp được đề xuất được triển khai trong MATLAB và so sánh với các phương pháp phát hiện đối tượng cổ điển. Kết quả mô phỏng xác nhận sự vượt trội của phương pháp đề xuất dựa trên một số tiêu chí đánh giá như độ chính xác, tỷ lệ phát hiện đúng và tỷ lệ báo động sai.
Từ khóa
#Nhận diện đối tượng #Hình ảnh viễn thám #SIFT #RANSAC #Thuật toán tăng trưởng vùng.Tài liệu tham khảo
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