OR-Skip-Net: Outer residual skip network for skin segmentation in non-ideal situations

Experiments were performed on the following eight open datasets for skin segmentation in different environments: hand gesture recognition dataset, event detection dataset, laboratoire d'informatique en image et systèmes d'information dataset, in-house dataset, UT-interaction dataset, augmented multi-party interaction dataset, Pratheepan dataset, and black skin people dataset. In addition, two other experiments were performed for gland segmentation from colon cancer histology images for the diagnosis of colorectal cancer using the Warwick-QU dataset and for iris segmentation using the Noisy Iris Challenge Evaluation - Part II dataset to explore the possibility of applying our method to different applications. Experimental results showed that the proposed OR-Skip-Net outperformed existing methods in terms of skin, gland, and iris segmentation accuracies.