Novel Adaptive Balloon Active Contour Method based on internal force for image segmentation – A systematic evaluation on synthetic and real images

• A new internal force to optimize the Adaptive Balloon Active Contour Method (AB ACM).
• Efficiency and effectiveness of segmentation by the AB ACM using synthetic images with different levels of complexity.
• Performance comparison of the proposed method with other traditional ACM.
• Application of the optimized algorithm in the segmentation of Industrial and Biomedical images.

Many studies have been conducted on digital image segmentation, seeking to overcome the limitations of different methods for specific applications. Thus, existing techniques are improved and new methods created. This paper proposes a new Active Contour Method (ACM) applied to the segmentation of objects in digital images. The proposed method is called Adaptive Balloon ACM and its main contribution is the new internal Adaptive Balloon energy that minimizes the energy of each point on the curve using the topology of its neighboring points, and thus moves the curve toward the object of interest. The method can be initialized inside or outside the object of interest, and can even segment objects that have complex shapes. There are no limitations as to its startup location. This work evaluates the proposed method in several applications and compares it with other ACMs in the literature. This new method obtained superior results, especially when the objects to be segmented were tubular and had bifurcations. Thus the proposed method can be considered effective in segmenting complex shapes in digital images and gave promising results in various applications.