Accelerate an OpenCV-based Android Application with KleidiCV
Introduction
Overview
Create a project and add OpenCV
Define the UI
Processing the Images
Summary
Next Steps

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About this Learning Path

Skill level:  Introductory
Reading time:  45 min
Last updated:  05 Aug 2026
Skill level:
  Introductory
Reading time:
  45 min
Last updated:
  05 Aug 2026
Author:Dawid Borycki
Arm IP:Cortex-A
Tags: Graphics Android Android Android Studio Kotlin Java
Author:
  • Dawid Borycki
Arm IP:
Cortex-A
Tags:
Graphics Android Android Android Studio Kotlin Java

Who is this for?

This is an introductory topic for developers who are interested in creating Computer Vision applications with OpenCV and KleidiCV on Android Devices.

What will you learn?

Upon completion of this Learning Path, you will be able to:

  • Describe what KleidiCV is, and what it can offer.
  • Create and configure a project to add OpenCV support.
  • Process images using OpenCV functionality.

Prerequisites

Before starting, you will need the following:

  • A development machine with Android Studio installed.
  • Familiarity with Android development concepts.
  • An Android smartphone.

Summary

AI-assisted

This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

Close
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You’ll build an OpenCV-based Android app and enable KleidiCV to accelerate image processing. First, you’ll configure the project, add an input image, and define a UI for results. Then, you’ll implement a modular pipeline with ImageOperation, ImageProcessor, and PerformanceMetrics. You’ll run operations such as blur, resize, or rotate, and inspect the processed image and performance statistics.

Frequently asked questions

AI-assisted

These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

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How do I know OpenCV and KleidiCV are correctly added to the project?
Build and run the app on your Android device. If image operations execute without errors and the UI shows updated output with performance metrics, the libraries are integrated.
Where do I put the input image, and what file types work?
Place the image under src/main/assets and name it img.png. Any kind of image file can be used; the app converts it to the required type during processing.
What should I check if the image doesn’t load in the app?
Confirm the assets folder path is src/main/assets and the file name matches img.png exactly, including case. Use the Project view in Android Studio to verify the location, then rebuild.
Which file do I edit for the UI, and what should I see after running?
Edit app/src/main/res/layout/activity_main.xml. When you run the app, you should see the defined layout, processed image, and performance metrics.
How can I switch or add image operations?
Select a different entry from the ImageOperation enum to apply another operation. To extend functionality, add a new enum value with its implementation and have ImageProcessor apply it.
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