A Connected-Tube MPP Model for Object Detection with Application to Materials and Remotely-Sensed Images

Tianyu Li (1) , Mary Comer (1) , Josiane Zerubia (2)

1 Purdue University [West Lafayette]
2 AYIN - Models of spatio-temporal structure for high-resolution image processing

In this paper, we propose a connected-tube model based on a Marked Point Process (MPP) for strip feature extraction in images. This model incorporates a connection prior that favors certain connections between tubes based on their mutual positional relationship. Moreover, this model can easily be combined with other geometric models to form a mixed MPP model for more complex detection tasks. The proposed tube model is applied to fiber detection in microscopy images by combining connected-tube and ellipse models. The ellipse model is used for detecting short fibers, while the longer fibers are detected by tube model. We also test the model on road and building detection in remotely sensed images.

Keywords: Mixed Marked Point Process; Stochastic; Modeling; Index Terms-Mixed Marked Point Process; stochastic modeling; connected tube model; fiber detection; road and building detection

Domains: Statistics [stat]; Engineering Sciences [physics]; Computer Science [cs]

Tianyu Li, Mary Comer, Josiane Zerubia. A Connected-Tube MPP Model for Object Detection with Application to Materials and Remotely-Sensed Images. ICIP 2018 – IEEE International Conference on Image Processing, Oct 2018, Athens, Greece. ⟨hal-02157080⟩