A Selective Segmentation Model Using Dual-Level Set Functions and Local Spatial Distance

被引：10

作者：

Rahman, Afzal ^{[1
]}

Ali, Haider ^{[1
]}

Badshah, Noor ^{[2
]}

Rada, Lavdie ^{[3
]}

Khan, Ayaz Ali ^{[4
]}

Hussain, Hameed ^{[5
]}

Zakarya, Muhammad ^{[6
]}

Ahmed, Aftab ^{[6
]}

Rahman, Izaz Ur ^{[6
]}

Raza, Mushtaq ^{[6
]}

Haleem, Muhammad ^{[7
]}

机构：

[1] Univ Peshawar, Dept Math, Peshawar 2512, Pakistan

[2] Univ Engn & Technol Peshawar, Dept Math, Peshawar 25000, Pakistan

[3] Bahcesehir Univ, Dept Math, TR-34349 Istanbul, Turkey

[4] Univ Lakki Marwat, Dept Comp Sci, Lakki Marwat 28420, Pakistan

[5] Univ Buner, Dept Comp Sci, Buner 19281, Pakistan

[6] Abdul Wali Khan Univ Mardan, Dept Comp Sci, Mardan 23200, Pakistan

[7] Kardan Univ, Dept Comp Sci, Kabul 1001, Afghanistan

来源：

IEEE ACCESS | 2022年 / 10卷

关键词：

Image segmentation; Mathematical models; Image edge detection; Computational modeling; Level set; Active contours; Motion segmentation; Euler-Lagrange equation; selective segmentation; level set function; local spatial distance; local similarity factor; IMAGE SEGMENTATION; ACTIVE CONTOUR; VARIATIONAL MODEL; INTERACTIVE IMAGE; FUZZY; FRAMEWORK; EFFICIENT;

D O I：

10.1109/ACCESS.2022.3152785

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Selective image segmentation is one of the most significant subjects in medical imaging and real-world applications. We present a robust selective segmentation model based on local spatial distance utilizing a dual-level set variational formulation in this study. Our concept tries to partition all objects using a global level set function and the selected item using a different level set function (local). Our model combines the marker distance function, edge detection, local spatial distance, and active contour without edges into one. The new model is robust to noise and gives better performance for images having intensity in-homogeneity (background and foreground). Moreover, we observed that the proposed model captures objects which do not have uniform features. The experimental results show that our model is robust to noise and works better than the other existing models.

引用

页码：22344 / 22358

页数：15

共 42 条

[1] A FAST LEVEL SET METHOD FOR PROPAGATING INTERFACES [J].