Inhomogeneity-embedded active contour for natural image segmentation

Inhomogeneity-embedded active contour (IEAC) is a technique used for natural image segmentation. The traditional active contour model, also known as the snake model, is a popular method for image segmentation. However, it is not effective for images with inhomogeneities such as intensity variations and noise.

IEAC overcomes this limitation by embedding inhomogeneity information into the active contour model. It uses an energy function that combines both the traditional snake model and image inhomogeneity constraints. The energy function is minimized to find the optimal contour that separates the object of interest from the background.

IEAC has been shown to be effective in segmenting natural images with inhomogeneities. It is useful in applications such as medical image analysis, where images often have inhomogeneities due to variations in tissue densities and imaging conditions.