A modified saliency detection for content-aware image resizing using cellular automata

It is often required that image resizing be done brightly in order to preserve important content. Some image resizing techniques like scaling and cropping fail to identify and protect important objects, or they produce non-photorealistic images. But content aware image resizing schemes aim to change image aspect ratios while preserving visually outstanding features. In this paper, a novel method for content aware resizing is presented. Seam carving, an effective image resizing algorithm, fails to protect important objects in images, when either the energy content of the objects are low with respect to their surroundings, or, the number of seams removed are very large. Using saliency map as the energy function in seam carving succeeds to identify important objects but it fails to recognize edges which results in removing borders of the objects during carving seams. In this paper we present a modified saliency map for seam carving using cellular automata. This modified saliency map leads to better results compared with its previous version, while concurrently achieving content aware image resizing.