Image processing applications in industry

If you are also interested in the field of image processing, go on and read this article. Image processing techniques have been around for about 40 years. But due to recent advancements in digital image production devices and also processing software it has gained a big recognition. I have gathered some information from different scholarly articles and will briefly write about different applications of image processing in the industry.

Image processing applications in industry
determining the crack type on wind turbine blade -Image from a paper by Zhang Huiyi

Image processing for defect detection in wind turbine blades

Structural health inspection has been widely applied in the operation of wind farms to find early cracks in wind turbine blades (WTBs). Increased numbers of turbines and expanded rotor diameters are driving up the workloads and safety risks for site employees. Therefore, it is important to automate the inspection process as well as minimize the uncertainties involved in routine blade health inspection.
Thus the research problem is how to accurately detect WTB surface flaws like cracks and erosion in a cost-effective manner. This is important since the detection results will directly affect the operation cost, repair methods and cost, and the turbine lifetime. The accuracy of blade inspection results has a direct impact on the lifetime of blades, inspection and maintenance costs, and the annual energy production of a turbine. [ read full article 1]

We are using drones to take high-resolution images from over the turbines and then we can use Image processing algorithms to first stitch the partial images of a blade and then perform a defect analysis and also determine the defect type.

Image processing applications in industry
The technology is used for detecting various colors for different materials and detecting big rocks

Image processing for Mining industry

A case study of ferruginous Indian manganese ore is presented. These ores show variation in their color owing to variation in chemical composition. These ores were studied in red, green, and blue color space, histogram analysis; textural analysis, and edge detection techniques were used for the separation of alumina lumps and to distinguish different ores. It shows acceptable results to carry out further studies for developing new cost-effective ore blending and ore sorting methodologies for the mineral industry. MATLAB 7·0 was used for image processing studies. [ read full article 2]

Another usage is using image processing techniques to detect big rocks. Detection of big rocks is an important, even critical, problem in the mining industry due to the risk of machine blockage causing high costs.

Image processing applications in steel industry
Temperature measurement by analyzing the radiation

image processing in the steel industry

The aim is to present a temperature measurement system based on CCD technology, which gives a linear response versus temperature and to display two industrial applications in which our systems has been involved to optimize and characterize the process. We present a short summary dealing with temperature evaluations from radiation measurements. We consider especially the problems of the surroundings, the atmosphere, and the emissivity assumption. After selecting a value for the emissivity, we show that the use of the CCD technology enables us to obtain high spatial and temporal resolution temperature imaging, and provides further information, mainly a linear response versus temperature, which will enable real-time implementation. Our measurement system based on CCD technology is particularly dedicated to processing control in the steel industry. CCD technology does not require a substantial cost and provides a lot of paramount information, enabling us to optimize some industrial applications based on accurate relative temperature measurements. [read full article 3]

computer vision for in food industry

Image processing in Food industry

The HSI technique has been investigated as a beneficial analytical method for fast, nondestructive, and none contact analysis for assessment of the quality and safety of meat and meat products, fruits and vegetables, aquatic products, cereals, and others. Several books and reviews summarizing the applications of HSI from different perspectives are also available; thus, only new applications since 2014 are discussed in this review.
Chemical and Physical Analyses, Moisture contents, Protein-related substances, Fat-related substances, Textural features, Food Safety Evaluation, Freshness evaluation, Defect detection, and many others are among the application of HSI technology applications in the food industry. [read full article 4]

Image processing applications in digital Cytology
Cytology branches of biology and medicine concerned with the structure and function of plant and animal cells.

Image processing for digital Cytology

This study is done by my Dear professor, Dr. Alberto Boschetto, and others. The software Mathematica has been selected due to its own characteristics and has been successfully used in a proposed process of image improvement applied on the snapshots with particular attention to (a) the focus emulation; (b) the visibility enhancement and (c) the feature recognition. The proposed methodology has been successfully investigated. It could be useful in tele-consulting, e-learning, in cooperative diagnosis, and in the applications of image quality improvements. [read full article 5]

Image processing in the automotive industry

High-speed cameras enable detailed fault analysis, especially in very fast-moving manufacturing processes. In the case of high-speed processes, the cameras’ superiority is obvious. But even in the case of mainstream manufacturing speeds, quality and process control is increasingly being transferred to imaging systems. Image processing ensures brilliant surfaces around the clock, micrometer-accurate assembly tolerances, and defect-free circuits on the increasingly prevalent chips & microcontrollers.

mage processing has not just established itself in automotive production. Reversing cameras protect against car body damage. At night, infrared cameras warn of unlit obstacles and pedestrians wearing dark clothing on the road. Stereo cameras and laser sensors measure the distance to vehicles driving ahead, detect animals suddenly running out into the road, thereby laying the foundation for cruise control systems and emergency brake assistants. Driverless test vehicles are already negotiating their way through city traffic without difficulty, driving in convoys on motorways, including performing overtaking and completely unprepared braking maneuvers, as well as journeys on secondary routes. Here too, the key to progress is the combination of optical sensors and intelligent image processing. The same goes for the use of imaging systems in traffic management centers and finally, police speed controls as well. The old green ‘speed camera boxes’ with a single camera are being supplanted by modern laser systems capable of monitoring several lanes simultaneously, thereby reining in speeding urban drivers. [Read full article 6]

If you like to know more about each field, references are linked at the end of each paragraph.

Thanks for reading this article.
If you know other image processing applications in the industry please write in the comments section and I will update this article.