Salient object detection in digital images based on superpixels and intrinsic features
Marlon-Alfonso Cuevas-Olvera, Rogelio Reyes-Reyes, Volodymyr I. Ponomaryov, Clara Cruz-Ramos · 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT) · 2018
Human visual system research and object detection in digital images have taken great relevance in the last years due to the different applications where it can be used, such as watermarking techniques to protect information, auto-focus on digital cameras, image compression, auto navigation, etc. This paper describes a saliency object detection method that uses intrinsic features of digital images: intensity, color, and texture. Also, Super Pixel Linear Iterative Clustering (SLIC) is employed to find the saliency object. The results have shown an accurate detection of the saliency object in digital images via comparison with well-known methods of the state-of-the-art. The results were evaluated through a subjective test using Mean Opinion Score (MOS).