Image Processing Components
Image processing is a term that has gained significant use in various industrial and non-industrial fields in recent decades. It refers to the analysis of images with the goal of extracting relevant information using related algorithms.
The components of an image processing system include imaging hardware and image analysis software. Image processing is an evolving technology, with yearly advancements in this field, driven by computer science, researchers aiming to improve existing techniques or introduce new ones for different industries. Today, even mobile software applications use image processing techniques to enhance images, verify identities, and modify images smartly.
Image Processing and Quality Control
The food industry benefits from image processing in quality control. These applications are grouped into two categories: color measurement and size determination and shape description. Color is a crucial component measured in quality control units to ensure uniformity in the final product. Colorimeter devices, which are now accessible with mobile apps, are examples of such techniques. In terms of size measurement and shape description, this method is integrated into sorting machines for raw materials and final products. Examples include separating fruits based on size in sorting lines or removing defective products before packaging. The combination of color and morphology plays a significant role in detecting contaminants in fast-paced processes. For instance, glass containers are checked for contamination by passing through an image processing chamber before being filled. Another use of image processing includes applying color measurement techniques online in baking ovens or dryers to prevent excessive color changes and regulate volume within defined limits.
Hardware and Software
Image processing relies on the equipment used, especially in areas where high-speed production processes occur. Consider an image processing system that scans a fast-flowing stream of flour through pipes and detects foreign particles. The camera in such a system must be able to capture high-frame-rate images per second, and after instant transmission to the image processing software, algorithms must be implemented to identify foreign objects from the flour particles in fractions of a second. Today, advancements in computer science and mechatronics have led to the design of high-speed robots for sorting and transferring products between different lines and packaging containers.
New Image Processing Techniques
A more advanced stage of image processing devices is hyperspectral imaging. This type of imaging helps obtain information from a product’s surface using both visible and non-visible wavelengths, which cannot be detected by the human eye. Researchers have successfully developed methods for more precise meat quality separation based on fat distribution and freshness, as well as early spoilage detection in fruits, based on this type of imaging. Advancements in this area could lead to the development of rapid, non-destructive online measurement equipment in production lines for more precise product control. Combining these techniques with ultrasonic and X-ray imaging methods can be particularly useful in identifying unwanted contaminants in packaging, which could cause irreparable harm to consumers.
Image Processing and Production Safety
In the industrial environment, image processing techniques are widely used to maintain product safety during production and storage. Human monitoring is always prone to error, whereas image processing algorithms instantly monitor the environment and alert observers to any changes. Today, the combination of artificial intelligence and image processing is used for material flow control, detection of operator’s errors, and temperature and level controls.
