About the client
Project description
Our solution
Image analysis pipeline
We tackled the challenge step by step, starting with the foundation: the image processing pipeline.
Vention’s team developed custom algorithms that scan, analyze, and gather metadata from images — which enabled Vexcel Imaging to quickly identify critical issues, like black pixels or corrupted files, and automatically exclude such pictures from their project pool. By automating this step, the team significantly reduced wasted time and effort on unusable images.
The pipeline also autonomously analyzes and modifies images, seamlessly combining them in the required order and format while accounting for differences in angles and perspectives. As a result, Vexcel Imaging specialists can dedicate their time to creating products and analyzing data rather than spending hours manually sorting through images.
AWS-based serverless automated solution
For projects like this, a serverless architecture often outperforms traditional server-based infrastructure for two main reasons:
- Cost-efficiency: With serverless, you pay only for what you use. When no images need processing, no Lambda functions are invoked, resulting in zero cost. Such flexibility is particularly beneficial for workflows with varying data loads.
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Instant scalability: A sudden influx of a million files? No problem. The solution instantly triggers additional functions and scales down quickly, eliminating the need for extra hardware or long wait times.
The workflow
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Initial filtering: The solution first analyzes the pictures, automatically excluding those with black pixels or corruption.
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Format standardization: Next, it converts all images into a unified format to streamline data gathering, analysis, and further processing or modifications.
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Image refinement: Mathematical models then analyze the images, identifying and comparing their borders. The system adjusts them through rotation or shearing, eliminating distortions and deviations to simplify processing.
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Metadata compilation: Finally, the images selected for the final product undergo metadata extraction. This data is stored in a separate file and provides comprehensive information about the areas captured in the images.
Why Lambda Functions?
Key stats
years of active collaboration
Vention team members
Image processing now takes hours — not weeks
Results
Tech stack
