Feed forward neural network training based interactive shopping for blind

Today shopping markets pay attention towards customer needs and services. Unfortunately the blind and vision impaired person are still incapable to access these environments without reliance. Assistive technology is trying to sway the living style of the blind by introducing support systems for routinely actions like reading, writing, walking, Web surfing, and shopping. However, still the blind have to count on others for personal accessories shopping. To overcome this problem, we designed and developed a feed forward talking accessories selector. Our system is trained using feed forward techniques with a feature level block-based multi-focus image fusion method to provide suggestions regarding product selection, fitness, and color combination, for instance in dress and jewelry. The evaluation of our system takes into account specialists opinions, such that statistical analysis shows similarity between both.