What I found most interesting about this class was the concept of machine vision. Engineering endeavors often mimic processes that occur naturally. Though I’ve come to this realization before, I’m still amazed when I learn about new research projects that are basically recreating nature. In a completely secular sense, its both frightening and fascinating how scientists can play God, creating artificial mechanisms to emulate that which has been created by unknown hand. Its just strange to think about, I mean, we don’t really know how the human eye was formed or how a hummingbird developed, but we seek to create things that behave in the same way. And when I think about the development of technology… its almost as though we’re forcing evolution upon our artificial creations. Like machine vision, for example. When it was first invented, its range of recognition was extremely narrow. Now we have orange harvesters that use machine vision to identify and pick oranges. The same thing happens in nature. A certain organism must adapt to change over time. Micro-evolution has been scientifically proven. So, in refining our nature-mimicking technologies, we essentially model nature as well.
Life is just like a giant circle… everything relates somehow.
Anyway, I looked up machine vision because I thought it was interesting.
Basically the way machine vision works is a smart camera (a digital camera, framegrabber, and processor) takes a picture of an object that is in position to be inspected. The camera will use lighting that is designed to illuminate parts of interest and downplay that which is not important. The framegrabber then translates the photo into digital format and stores it in the computer’s memory. Machine image software will then reduce noise or perform binarization (conversion of gray shades into black and white). If the machine vision is being used on an assembly line or performing some other inspection, it will count the desired features on the object (defects, markings, dimensions, etc.) and either pass or fail it, according to programmed specifications.
Presently, machine vision is used mostly in single, repetitive tasks such as those involved in product inspection, safety monitoring, and quality control. To a certain extent, machine vision is more reliable than human vision in terms of inspection, because humans are susceptible to distraction and lack of focus. But machine vision is still a long way from even approaching human adaptability, as most machine vision systems cannot adjust to variability in lighting or image degradation.