The differences between machine vision testing and human visual perception in today's market
Release date:
2015-11-13 00:00
Source:
Human vision possesses highly advanced intelligence, enabling it to leverage logical analysis and reasoning when identifying objects, as well as to discern underlying patterns. Moreover, the human visual system exhibits exceptional color-discrimination capabilities—but this ability is easily influenced by psychological factors, making it difficult to quantify accurately. At the same time, our eyes aren’t very adept at distinguishing shades of gray; typically, we can only perceive around 64 distinct grayscale levels. Additionally, our spatial resolution isn’t stellar either, often struggling to detect even the tiniest objects clearly.
Machine vision systems are different—they boast exceptional grayscale resolution capabilities. Today’s technology already supports up to 256 grayscale levels, and imaging systems can even handle 10-bit, 12-bit, or 16-bit grayscale formats. Moreover, the latest machine vision systems come equipped with 8K line-scan cameras or 4K x 4K area-array cameras, paired with a variety of high-quality optical lenses, enabling observation of objects ranging from celestial bodies to microscopic structures as small as microns.
Moreover, machine vision systems exhibit exceptional adaptability, making them relatively undemanding in terms of environmental requirements. Additionally, protective devices can easily be added based on specific needs. The system also boasts an incredibly fast shutter speed—capable of reaching around 10 microseconds—and its high-speed cameras can achieve frame rates exceeding 1,000 fps. On top of that, the computer processing speed is remarkably swift as well.
However, machine vision isn’t yet very strong in terms of intelligence—while we can leverage artificial intelligence and neural network technologies, it remains challenging for machines to reliably recognize objects. And although machine vision excels at quantifying color, current hardware limitations still make it difficult to distinguish between subtle color variations.
