Digital image processing is a technique that takes information and data from a digital image to either enhance or edit the original image or to analyze and compare to other data in a database. For the purpose of this article, we are going to focus on the later application and its potential.
Real world applications
Image processing is not new, but its potential and opportunities continue to grow.
Currently, the most popular application of image processing is for plant identification. A picture of a leaf can be taken (on a phone or elsewhere) and uploaded to the tool. From there, the original image will be compared to those in the database. Once a certain number of similarities are found, the plant in the image can be identified.
Image comparison can also be used in the medical field, for example, to take a picture of a mole to determine if it is worrisome.
While X-rays, CT scans, UV imaging and the like have been in place for decades, including their respective image processing machines, innovative uses for the technologies are emerging. Recently, ePeak helped a healthcare company with their medical device that analyzes images of cells to compare to a database. The purpose of this application is to aid in the diagnosis process in an accurate, efficient way. More than just being able to take and produce the image, medical devices can have the potential to save doctors and practitioners time and resources.
Face and Object Detection
Similar to the examples in the Comparisons group, face and object detection tools scan images to detect what is represented in the photograph. This is commonly used in many current smartphones as an unlocking feature, or within photo editing applications to categorize and sort by content.
How digital image processing works
The complicated process of digital image processing can be broken down into three essential steps:
Step 1: Image Import
Relatively self-explanatory, in the image import stage, a digital image is uploaded to the image processing system. This is the extent of the manual work the user needs to do.
Step 2: Analysis
Once the system receives the digital image, the tool will extract data from individual components of the image. It will then compare that with data extracted from other images in its database.
Ensuring the database is robust, accurate, and able to be easily organized is essential. ePeak has collected and organized the data for image processing databases in the past and has the expertise to give you peace of mind while building your database.
Step 3: Data Output
Based on the analysis in Step 2, the image processing system will have some kind of report to communicate with the user. This can be the results from the image comparisons; it can be a deeper analysis into what those comparisons may mean about the original image; in a more enhance/edit application of image processing, this is when a new image is produced.
You will need to understand this analysis in a meaningful way. ePeak can take the data from your image processing analysis and display it in an easy-to-digest dashboard. Data visualization will give you quick access to the insights you need.
Different digital image processing methods
Just as the use cases for digital image processing varies drastically, the different methods to process an image also differ. A few of the most common processes are highlighted below.
Analysis: extracts features to compare data in a database
- Independent component analysis: separates components to analyze in subcomponents
- Linear filtering: processes time-varying input
- Neural networks: computational models in machine learning
- Self-organizing Maps: classifies images into categories
Editing: via graphic software tool
Restoration: processing a broken/corrupt image, filling in the missing information, regaining the original image
Wavelets: math function for compressing image
Digital image processing is a growing technology with expanding potentials. If you’re interested in implementing image processing methods, or enhancing your current processes, contact ePeak to learn more.