Computer Vision in Defect and Anomaly Detection

Computer Vision in Defect and Anomaly Detection

Have you ever thought of having doctors for machines? Yes, you read that right.

Computer Vision is a doctor for machines that enable computers to detect detailed irregularities in machines at a speed surpassing the human vision capability. In this particular article, we are going to highlight the characteristics of computer vision and its effectiveness. So, let’s get started!

Every industry relies on new technologies to overcome the problems faced by traditional methodologies. This is where computer vision pitches in. Computer vision is known to detect various anomalies in a single shot without any manual tuning and handles complex patterns. Its implementation not only eases the process of defect finding but also reduces the time and cost of manufacturing. In most cases, quality assurance cost ranges from 15-40% of the total sales revenue which can be drastically reduced (almost half) by utilizing deep learning.


Some Benefits of Computer Vision in Defect Detection:

  •   Greater customer satisfaction
  •   Good market reputation
  •   A step ahead of competitors
  •   Reduced cost and time
  •   Almost 100% accuracy
  •   Tailored for specific need
  •   Higher profits


How does it works?

The process is similar to the general machine learning process that involves teaching the machine with tabular data. The only difference is that in computer vision, the machine is trained with the help of image data sets (which are stored in the form of matrices). For black and white images there are values in the matrices that define its darkness, but for colored images, there are three colors which are identified, namely red, blue, and green. The values in the matrices change w.r.t change in the intensity of the colors.

The first step is to train the system with the help of error-free samples so that the machine knows the quality that it is looking for. After this, the machine is trained to detect defects and anomalies easily. Eventually, with improvements in the algorithms, comes a stage, where the even tiniest of defects become quantifiable.


Steps involved in Defect Detection:

  • Collecting data with the best and the worst defects traceable
  • Browsing of training sets
  • Modeling training and specifying every possible parameter
  • Starting model recognition and exploring the final results



The whole process contributes to saving high manual labor cost, time, and money. All these factors amalgamate to deliver better customer satisfaction with higher ROI and reduced resource consumption.

One thing which has to be kept in mind is that the actual deep learning architecture (number of layers and node connectivity) differs according to the complexity of the problem, materials involved and the industry targeted. However, U-Nets architecture is one of the most plausible and promising possibility.


Few Industries that are/can leverage Computer Vision for Defect Detection:

  • Medical – The technology can help in tracing any deviation from the source data and audit the results to optimize them.
  • Aerospace – Computer vision is already being leveraged by companies within the Aerospace industry to maintain tough industry standards and regulations.
  • Automotive – This industry is known for its touch quality checks. Hence, computer vision can play an enormous role to detect defects in both interiors and exteriors of the vehicles.
  • Textiles – There are a number of processes which are followed in the textile industry before delivering the final output. Computer vision can help the industry in finding faults and defects at the starting of the production process to save cost.


To sum it up:

To businesses, Computer Vision in Defect and Anomaly Detection holds a tangible value which is to find problems that would otherwise be hidden and respond to them instantly.

At Avyuct, we offer computer vision solutions that find applications in various industries like aerospace, manufacturing, medical, automotive, textile, etc. Our solutions are user-friendly. If you wish to know the application of computer vision, deep learning or data sciences in your industry, connect with our subject experts!


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