Upgrading your core infrastructure is rarely just a “check the box” task. For many development teams, moving from one Java Version to another feels like navigating a minefield. You expect performance gains and security patches, but you don’t expect your core image processing to suddenly break.
When your application relies on high-accuracy image rendering, a “small” library change in the JDK can lead to a high-priority system failure.
The Migration Trap: Lack of Standard Support
When “Standard” Support Vanishes
This was the reality for one of our enterprise customers working in the insurance industry. During their migration to Java 11, they hit a wall: the native Java support for a specific TIFF format (containing an opaque attribute) had been removed.
The Real-World Impact: System Breaks and Rollbacks
The result? Sudden runtime exceptions. Documents that used to open perfectly were now appearing as blank pages. To keep the lights on, the team was forced to route users back to aging Java 8 servers, a temporary fix that stalled their security and modernisation goals.
They weren’t just looking for a new library; they were looking to restore a foundation that had been pulled out from under them.
The Accuracy Ceiling: Why 85% Isn’t Enough
Precision Engineering: Beyond Good Enough
For another client in the software engineering space, the challenge wasn’t migration, but a matter of precision. They were building a facial recognition project that required near-perfect accuracy when opening, cutting, and blurring images.
The High Stakes of Facial Recognition Accuracy
They found that free, open-source libraries could only handle about 85% of their real-world cases. In the world of AI and security, a 15% failure rate makes a project non-viable.
They were at a crossroads: either find a way to support the “obscure” formats or abandon Java entirely for a different language.
Bridging the Technical Debt Gap
The Cost of Doing Nothing vs. Building In-House
The common thread here is the need for a “commercial-grade” safety net. When standard or free libraries fall short, the cost of building a fix in-house is often prohibitive. It requires months of specialized engineering time that most teams simply don’t have.
Why Commercial Libraries Are a Strategic Choice
By integrating JDeli, these teams were able to:
- Restore Backward Compatibility: Act as a direct, drop-in replacement for native Java Image IO.
- Guarantee Accuracy: Move from an 85% success rate to over 90% (and higher), covering the edge cases that crash other libraries.
- Maintain Security: Proceed with the Java 11 upgrade to meet security mandates without losing the ability to process legacy documents.
Technical Implementation: Restoring Image IO Stability
From Complex Workarounds to Drop-in Replacements
The beauty of the JDeli Java PDF library is that the code often gets simpler, not more complex. Here is how these teams addressed their compatibility and accuracy issues.
Code Example: Replacing ImageIO with JDeli for TIFF Compatibility
With JDeli you have drop in replacement for ImageIO with a simple API:
- Add JDeli to Your Project: Add JDeli to your class or module path. (download the trial jar)
- Register the TIFF format for JDeli use
ImageIOSupport.registerReader(ImageIOSupport.InputFormat.TIFF);
- Read TIFF files in pure Java
BufferedImage bufferedImage = JDeli.read(tiffImageFile);
Code Example: High-Accuracy Image Processing for Specialised Applications
JDeli can help you manipulate images (in many different ways) with maximum accuracy, in pure java.
- Add JDeli to Your Project: Add JDeli to your class or module path. (download the trial jar)
- (Example) Scale images in Java
ImageProcessingOperations operations = new ImageProcessingOperations();
// You can chain several operations here such as scale, blur, etc
operations.qualityScale(1.2);
// Apply the operations to a BufferedImage
BufferedImage modifiedImage = operations.apply(BufferedImage originalImage);
When system stability and security are paramount, you can’t afford to let “standard” library limitations dictate your roadmap.
Whether you are navigating a major migration or pushing the limits of image analysis, the goal is the same: software that just works, every time.
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