Segmentation Algorithm of the Valid Region in Fisheye Images Using Edge and Region Information

In this paper, we propose a method to segment the valid region of fisheye images. First, we construct an objective function with three terms, which are the region driving term, the edge driving term and the length regularization term. Second, we minimize this objective function by a modified gradient descent method to find the best segmentation result. Our method can achieve valid region segmentation by making use of both region information and edge information. Experiments show that the proposed method can deal with blurred edges, halation noise and incomplete valid region problems.

[1]  Yang Liu,et al.  Fast and robust ellipse detector based on edge following method , 2019, IET Image Process..

[2]  Homer H. Chen,et al.  360° Video Stitching for Dual Fisheye Cameras , 2019, 2019 IEEE International Conference on Image Processing (ICIP).

[3]  Li Bo Fisheye Image Contour Extraction Algorithm Based on Region Growing , 2010 .

[4]  Viorica Pătrăucean,et al.  Joint A Contrario Ellipse and Line Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Ying Ding,et al.  Robust contour extraction of fisheye images for image-based virtual reality , 2010, 2010 3rd International Congress on Image and Signal Processing.

[6]  Bin Fang,et al.  B-Spline based globally optimal segmentation combining low-level and high-level information , 2018, Pattern Recognit..

[7]  Mengxue Xu Comparison and Research of Fisheye Image Correction Algorithms in Coal Mine Survey , 2019 .

[8]  Yandong Tang,et al.  Automatic Segmentation of the Papilla in a Fundus Image Based on the C-V Model and a Shape Restraint , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[9]  Yun Fu,et al.  Arc-Support Line Segments Revisited: An Efficient High-Quality Ellipse Detection , 2018, IEEE Transactions on Image Processing.

[10]  Homer H. Chen,et al.  Image Stitching for Dual Fisheye Cameras , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[11]  Madhukar Budagavi,et al.  Dual-fisheye lens stitching for 360-degree imaging , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[12]  Bin Fang,et al.  A variational approach to liver segmentation using statistics from multiple sources , 2018, Physics in medicine and biology.

[13]  Lei Zhang,et al.  Active contours with selective local or global segmentation: A new formulation and level set method , 2010, Image Vis. Comput..

[14]  Wang Da-yu Research of Virtual Navigation Based on Fisheye Image , 2007 .