Journal ArticleDOI
Image Processing on Raspberry Pi for Mobile Robotics
K. Horak and L. Zalud
- pp 494-498
TLDR
A cheap framework for fast image processing in real-time including feature extraction and image transformation methods, frequently used not only in robotics are designed and tested on the Raspberry Pi 2 equipped with a native camera board.Abstract:
We have designed a small robot called Cube for simple robotics tasks and students works. The Cube carries only small and lightweight computational platform Raspberry Pi equipped with a camera. This paper serves as an introduction to using image processing methods on a Raspberry Pi platform via Simulink in Matlab. We have designed a cheap framework for fast image processing in real-time including feature extraction and image transformation methods. In the paper a several selected methods frequently used not only in robotics are implemented and tested on the Raspberry Pi 2 equipped with a native camera board. Algorithms for edge, corner and line detection have been implemented by using Simulink with the Computer Vision System Toolbox and other in-build tools.read more
Citations
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An Asus_xtion_probased indoor MAPPING using a Raspberry Pi with Turtlebot robot Turtlebot robot
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Book ChapterDOI
Embedded Vision Systems: A Review of the Literature
Deepayan Bhowmik,Kofi Appiah +1 more
TL;DR: A comprehensive review of embedded vision algorithms and applications over the past decade, including image acquisition, preprocessing, object detection and tracking, recognition as well as high-level classification is presented.
Proceedings ArticleDOI
Real-Time Image Processing Method Using Raspberry Pi for a Car Model
TL;DR: The development of a car model that can detect edge, line, and corner of the road image and also the model can detect the red color of a traffic light image is presented.
References
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Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Book
Image Processing: Analysis and Machine Vision
TL;DR: The digitized image and its properties are studied, including shape representation and description, and linear discrete image transforms, and texture analysis.
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A review on image segmentation techniques
Nikhil R. Pal,Sankar K. Pal +1 more
TL;DR: Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches, which addresses the issue of quantitative evaluation of segmentation results.
Proceedings Article
Image Processing
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Book
The Image Processing Handbook
TL;DR: The Image Processing Handbook, Seventh Edition delivers an accessible and up-to-date treatment of image processing, offering broad coverage and comparison of algorithms, approaches, and outcomes.