Image-to-MIDI mapping based on dynamic fuzzy color segmentation for visually impaired people

In this paper, the RGB ratio is defined according to a reference color so that an image can be transformed from a conventional color space to the RGB ratio space. Different to traditional distance measurement, a road color model is determined by an ellipse area in the RGB ratio space enclosed by the estimated boundaries. The proposed dynamic fuzzy logic, where fuzzy membership functions are defined according to estimated boundaries, is introduced to implement clustering rules, such that each pixel will have its own fuzzy membership function corresponding to its intensity. A basic neural network is trained and used to achieve parameter optimization. Experimental results for road detection demonstrate the robustness of the proposed approach to variations in intensity. To provide obstacle information, especially for visually impaired people, Musical Instrument Digital Interface (MIDI) is introduced as the sound generator, and image-to-MIDI mapping algorithm is proposed. Experimental results show that the proposed method can adapt to various road types, and the resulting audio information successfully indicates the position and size of obstacles.

Research highlights
► Intensity and color information are effectively described in the RGB ratio space.
► Color segmentation with dynamic fuzzy logic performs robustness to road types.
► Fuzzy c-means line-clustering technique generates clustering number autonomously.
► Image-to-MIDI mapping makes audio instruction more effective to the visually impaired.