Optical sorting
Depending on the types of sensors used and the software-driven intelligence of the image processing system, optical sorters can recognize an object's color, size, shape, structural properties and chemical composition.
[5] Today, optical sorting is used in a wide variety of industries and, as such, is implemented with a varying selection of mechanisms to assist in that specific sorter’s task.
Monochromatic cameras detect shades of gray from black to white and can be effective when sorting products with high-contrast defects.
The interaction of different materials with parts of the electromagnetic spectrum make these contrasts more evident than how they appear to the naked human eye.
This structural property inspection allows lasers to detect a wide range of organic and inorganic foreign material such as insects, glass, metal, sticks, rocks and plastic; even if they are the same color as the good product.
[8] For example, lasers can detect chlorophyll by stimulating fluorescence using specific wavelengths; which is a process that is very effective for removing foreign material from green vegetables.
[9] Sorters equipped with cameras and lasers on one platform are generally capable of identifying the widest variety of attributes.
Cameras are often better at recognizing color, size and shape while laser sensors identify differences in structural properties to maximize foreign material detection and removal.
When complemented by capable software intelligence, a hyperspectral sorter processes those fingerprints to enable sorting on the chemical composition of the product.
Once the sensors capture the object's response to the energy source, image processing is used to manipulate the raw data.
The art and science of image processing lies in developing algorithms that maximize the effectiveness of the sorter while presenting a simple user-interface to the operator.
The considerations that determine the ideal platform for a specific application include the nature of the product – large or small, wet or dry, fragile or unbreakable, round or easy to stabilize – and the user's objectives.
These more sophisticated sorters often feature advanced cameras and/or lasers that, when complemented by capable software intelligence, detect objects' size, shape, color, structural properties, and chemical composition.
These sorters are often most suitable for nuts and berries as well as frozen and dried fruits, vegetables, potato strips and seafood, in addition to waste recycling applications that require mid-volume throughputs.
Belt sorting platforms are often preferred for higher capacity applications such as vegetable and potato products prior to canning, freezing or drying.
A fifth type of sorting platform, called an automated defect removal (ADR) system, is specifically for potato strips (French fries).
For products that require sorting only by size, mechanical grading systems are used because sensors and image processing software is not necessary.
[16] However, this science is not limited to coffee beans; food items such as mustard seeds, fruits, wheat, and hemp can all be processed through optical sorting machines.
The technology meticulously inspects tablets and capsules to detect and remove defects such as cracks, chips, discoloration, and size deviations.
By automating the inspection process, optical sorters reduce human error and labor costs while maintaining compliance with stringent regulatory standards, ultimately safeguarding consumer health and brand reputation.
[22] Additionally, in medical laboratories, optical sorters aid in the sorting and analysis of biological samples, such as cells or bacteria cultures.
The high-speed analysis and sorting capabilities of these machines improve diagnostic accuracy, research efficiency, and overall laboratory productivity.
