The mobile networks seem to have a steady future in the direction of the recent emergence of socially aware cognitive mobile networks. Their style and design are specifically made in improving shared spectrum space access, in cooperative spectrum sensing, and in enhancing device-to-device communications. Socially aware mobile networks do have enough potential to amass sufficient returns in the efficacy of the spectrum and also to march and gain a considerable amount of increase in the capacity of the network. Even though there are lot of gains in its potency to be reaped yet, still there seems to be enough challenges that are both business- and technical-related that have to be taken care of. This chapter delves into the cognitive radio (CR) and its social relations and also makes sufficient exploits in establishing a scheme that will be based on social-based cooperative sensing scheme (SBC).

Salient region detection and segmentation from biological images is often a crucial step for image understanding. The initial contour selection during segmentation being a competent task and wrong differentiation between the foreground and background colours are compromised. In this paper, improved cell detection is introduced by using a region-based cell detection and segmentation method called Histogram Colour Contrast Seed Point Selection (HCC-SPS). In each pixel, the HCC model is able to group similar colour values, therefore addressing colour contrast in visual signal, resulting in accurate desired edge points. Second, considering the energy function, region-based seed point fine tunes the salient value and makes differentiation between salient and background points easier. Third, due to salient mapping function with pixel representation, the segmentation of biological images, done accurately. The results are compared with the existing system based on the parameters such as accuracy rate, segmentation time and mapping functions.