Cuckoo Search in Image Visibility Improvement: A New Way

Engineering design optimization problems are frequently found highly non-linear with complex constraints design variables. These constraints can be expressed in terms of range, structure similarity, signal-to-noise relationship, etc in computer vision. Image processing problems can be reformulated as optimization problems, especially bio-inspired problems. By selecting and designing proper object function, restoration, segmentation, thresholding etc of images could be done with superior results. Meta-heuristics are fit for those cases for optimal solutions. Cuckoos are recognized as charming birds due to its beautiful sounds and also their aggressive reproduction strategy. Moreover, few species such as the ani and guira cuckoos lay their eggs in communal nests removing others' eggs increasing the hatching probability of their own eggs. It is found in nature that searching for food is a random or quasi-random system for animals. Surprisingly, research shows that the foraging path of an animal follows a random walk rigorously accompanying current location and transition probability to the next location. Thus, this random walk can be mathematical modeled efficiently.

Autorentext

Sangita Roy è professore associato presso il Dipartimento ECE del Narula Institute of Technology, India. Ha un'esperienza di insegnamento di oltre ventisei anni. È stata per due anni alla Bells Controls Limited (industria della strumentazione) e per due anni al West Bengal State Centre, IEI (Kolkata) come coordinatore tecnico.