NIMS has developed an ionic machine vision device capable of increasing the edge contrast between the darkest and lightest areas of a mage in a manner similar to human vision. This very first synthetic mimicry of human optical illusions was achieved using ion migration and interaction within solids. It may be possible to use the apparatus to develop compact and energy efficient visual detection and image processing hardware systems capable of processing analog signals.
Many developers of artificial intelligence (AI) systems have recently shown great interest in researching various sensors and analog information processing systems inspired by human sensory mechanisms. Most AI systems researched require sophisticated software / programs and complex circuit configurations, including custom designed processing modules equipped with arithmetic circuits and memory. However, these systems have drawbacks in that they are bulky and consume a lot of energy.
The NIMS research team recently developed an ionic machine vision device composed of a network of mixed conductive channels placed at regular intervals on a solid electrolyte. This device simulates how human retinal neurons (i.e. photoreceptors, horizontal cells, and bipolar cells) process visual signals by responding to input voltage pulses (equivalent to electrical signals from photoreceptors) . This causes the ions to migrate into the solid electrolyte (equivalent to a horizontal cell) through the mixed conductive channels, which then changes the output channel current (equivalent to a bipolar cell response). Using such steps, the device, regardless of software, was able to process the input image signals and produce an output image with increased edge contrast between darker and lighter areas in a similar fashion. to how the human visual system can increase edge contrast. between different colors and shapes by means of visual lateral inhibition.
The human eye produces various optical illusions associated with tilt angle, size, color and movement, in addition to darkness / brightness, and this process is believed to play a crucial role in the visual identification of different objects. The ionic machine vision device described here can potentially be used to reproduce these other types of optical illusions. The research team involved hopes to develop visual detection systems capable of performing human retinal functions by integrating the device in question with other components, including photoreceptor circuits.