Another paper was written by D.Yang et al, in order to develop a real time assistive system for blind people. The name of the device was given after its algorithm named EBCOT which stands for Embedded Block Coding with Optimized Truncation. The main idea of this algorithm is to apply two-tier coding and optimal wavelet base. The ability of coding with embedded block and minimum ratedistortion are the main features of this algorithm. The system receives real time images via a regular camera, processes them and the resultant sounds are transferred to the headphones. Finally they compared their system with existing compression methods, such as SPIHT and EZW. The results showed that EBCOT algorithm has the highest time efficiency among existing methodologies.
Another paper written by P. Codognet and G. Nouno presents a real time system that generates sound according to the blinking lights which were placed into the highest skyscrapers in Tokyo. Red Light Spotters Project encompassed artistic creation process embedding image tracking and beat prediction algorithms. The key idea was to achieve an emergent rhythmic process for the musical creation and generative music. Results showed that the system could be applicable to any other city under one condition.
the necessity of rhythmic flow of lights. One of the studies related with sound to image mapping was written by K. Abe et al. In their work, they developed a sound classification method based on timefrequency image processing. They classified sound in four different classes: “Speech”, “Noise”, “Speech in Noise” and “Classical Music”. The initial idea was to develop a system that could calibrate the hearing aids automatically according to the acoustic environmental changes. Their algorithm generates images from the sounds that are coming to hearing aids. According to the characteristics of the images, sound is
classified into four classes. The authors state that the proposed method has a possibility to establish a sound classification in
hearing aid system as the first and rough trial.
Another paper about image to sound conversion techniques was written by A.
Fusiello et al [7]. Sonification techniques were used to create a system named Multimodal Electronically Travel Aid Device.
Their system includes an earphone, a portable computer, a laser pointer which would be used to estimate the z-depth. Finally, a stereo camera pair was used in order to generate stereo vision. The algorithm tracks down the sound signals, applies 3D reconstruction and with the help of sonification techniques sound is generated. Results have shown that laser usage could create problems about the analysis of depth, but the overall results were satisfactory. In one of the researches about auditory display [8], they stated that image can be visualized as a two dimensional pixel-space and with each pixel having a discrete value. They claimed that an image can be represented as a threedimensional matrix having three indices: x-position, y-position and its intensity value. For this reason they conclude that image sonification can be applicable to real life. With the usage of image sonification, data can be converted from a static twodimensional domain to a one dimensional time domain. The helical coordinate system [9] could be used for this transformation. One of comparison studies about image to sound conversion methodologies is published by R. Sarkar et al[10]. They stated that the initial attempts of image to sound
mapping failed because of the ignorance of the principles of psychoacoustic during the implementation of previously proposed systems and algorithms. They concluded that the multi channel image data analysis will be in demand for the upcoming researches for image sonification. It is recognized that the intensity, the frequency and the temporal discrimination of static
audible sounds have more importance in image to sound mapping as stated on certain articles [11]-[13]. Further studies proved that one to one mapping from image to sound can ensure the preservation of visual information [1].