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Trần Như Ý, Nguyễn Viết Hưng, Nguyễn Quốc Huy, Phạm Thế Bảo, NGUYỄN VIẾT HƯNG(1)

Phân đoạn ảnh và ncuts

Image segmentation and ncuts

Tạp chí Khoa học - Đại học Sư phạm TP Hồ Chí Minh

2021

6

1100-1112

1859-3100

Eigenvalue, Graph-cut, Ncuts

Eigenvalue, Graph-cut, Ncuts

Trong nhiều thập kỉ qua, nhiều công trình nghiên cứu khoa học đóng góp không ngừng trong lĩnh vực thị giác máy tính nói chung cũng như nghiên cứu phân đoạn ảnh nói riêng. Trong đó, phân đoạn ảnh là quá trình tiền xử lí quan trọng trong hầu hết các ứng dụng xử lí ảnh. Chúng tôi tóm tắt và đánh giá các kĩ thuật phân đoạn ảnh và phân chia các kĩ thuật này thành các nhóm gồm: kĩ thuật dựa trên phát hiện cạnh/biên, kĩ thuật phân ngưỡng, phương trình vi phân, phương pháp gom nhóm, kĩ thuật dựa trên phân hoạch đồ thị. Tiếp theo, chúng tôi trình bày ưu điểm và khuyết điểm của thuật toán Ncuts, là thuật toán kinh điển khá phổ biến trong phân đoạn ảnh dựa trên đồ thị. Thuật toán Ncuts (Shi, & Malik, 2000) được đưa ra năm 2000 nhưng đã được áp dụng thành công và cho kết quả tối ưu cho nhiều ứng dụng xử lí ảnh cũng như các ứng dụng khoa học kĩ thuật.

In the past decades, many studies have been conducted in computer vision and image segmentation. Image segmentation is the process of image preprocessing in most image processing applications. We summarize and evaluate image segmentation techniques and categorize them, including edge detection, thresholding, partial differential equation, clustering, and graph-based. Next, we present the pros and cons of the Ncuts algorithm, which is typical of graph-based image segmentation. The Ncuts algorithm was introduced in 2000 and showed optimal results for image processing and other applications.

TTKHCNQG, CTv 138

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