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Related Experiment Video

Updated: May 29, 2026

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

Projection-based geometrical feature extraction for computer vision: algorithms in pipeline architectures.

J L Sanz1, I Dinstein

  • 1Department of Computer Science, IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

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This study introduces new algorithms for image analysis features, optimizing pipeline architectures without needing dedicated hardware. These methods leverage the Radon transform for efficient image processing and computer vision applications.

Area of Science:

  • Computer Vision
  • Image Processing
  • Scientific Computing

Background:

  • Traditional image analysis often relies on dedicated hardware and random access memories.
  • Existing methods for extracting features like Hough transform and principal components can be computationally intensive.
  • Pipeline architectures offer potential for efficient image processing but require specialized algorithms.

Purpose of the Study:

  • To present novel algorithms for computing image features suitable for pipeline architectures.
  • To demonstrate image analysis techniques that eliminate the need for random access memories and dedicated hardware.
  • To illustrate the application of the Radon transform within a pipeline projection engine framework.

Main Methods:

  • Algorithms for image features including projections, convex hull approximations, Hough transform, diameter, moments, and principal components.

Related Experiment Videos

Last Updated: May 29, 2026

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

  • Development of feature computation methods optimized for pipeline implementation.
  • Utilizing the Parallel Pipeline Projection Engine (PPPE) architecture for algorithm execution.

    • Main Results:

    • Algorithms effectively compute image features without requiring random access memories or dedicated hardware.
    • Demonstrated effectiveness of new algorithms on conventional short-pipelines for image analysis.
    • Successful integration of Radon transform-based algorithms within the PPPE framework.

    Conclusions:

    • The proposed algorithms offer an efficient and hardware-independent approach to image analysis feature extraction.
    • The PPPE architecture provides a powerful platform for projection-based computer vision and image processing.
    • The Radon transform is a versatile tool for image analysis within specialized pipeline architectures.