Computer vision systems follow a basic structure that can be divided into three stages illustrated in Figure 1: low, intermediate, and high level of processing. Ĭomputer vision can be understood as the science that develops theory and algorithms to extract useful information about an object or scene within an image, for further analysis.
Computer vision systems (CVS) intend to emulate this sophisticated and dynamic vision system whose operation is very natural and transparent. Even to this day, there are many unknowns about its operation and even its biological purpose. On the other hand, the brain is much more complex. The lens regulates the focus for near and far objects as they become more or less globular. The cornea and lens focus light rays at the back of the eye. In general, the human vision system can be described as follows: the eyes are composed of the eyeball and the muscles that control its position. The visual perception of the human being is basically composed by the interaction between the eyes and brain.
That is why trying to emulate these capabilities is a huge challenge. The human being has another essential organ, the brain, which is the main processing unit, responsible for receiving, processing all information, making decisions, and coordinating actions in a synchronized, a fast, and an efficient manner. Some of the senses manage to partially or totally regenerate from time to time. The human senses are complex systems within the human body, which in turn are formed by an immense number of well-adapted and calibrated sensors with a very wide range of operation to carry out specific tasks, in addition to adapting and interacting with each other. The perception of the human being is an incredible skill composed of five senses: sight, ear, smell, taste, and touch. The way to perceive such an enormous amount of information is achieved through the senses. The evaluation of what surrounds us is done through light, colors, shapes, textures, and intensities, among other characteristics, which originate from different natural phenomena that give rise to spectacular scenes that are visually striking to observe. Based on former paragraphs, we could say that machine vision systems are appropriate to improve the actual agricultural systems making them more useful, efficient, practical, and reliable. A machine vision system is the combination of several high-tech techniques, including both hardware and software, used to acquire, process, and analyze images on a machine, which contributes with a set of tools for the extraction of features, such as color and dimension parameters, texture, chemical components, disease detection, freshness, assessment, modeling, and control, among others. Currently, along with the new technological advances in electronics, computer systems, image processing, pattern recognition, and mechatronics, it has arose the opportunity to improve machine vision systems development with affordable implementations at lower cost.
It was in the early 1960s when machine vision systems initiated researchers and developers have worked on building machines that perform tasks of acquisition, processing, and analysis of images in a wide range of applications for different areas.