Length: 2 Days
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Digital Image Processing Workshop by Tonex

Biomedical Imaging and Signal Processing

This comprehensive workshop by Tonex delves into the intricate world of Digital Image Processing (DIP), equipping participants with essential knowledge and practical skills. Through hands-on exercises and real-world applications, attendees will gain proficiency in manipulating and enhancing digital images.

Tonex’s Digital Image Processing (DIP) Workshop offers a comprehensive exploration of fundamental concepts and practical skills in image manipulation. Geared towards professionals in computer vision, photography, and biomedical imaging, this hands-on workshop covers image enhancement, filtering, segmentation, and restoration.

Participants delve into advanced topics such as image compression, machine learning for image recognition, and real-world applications. By the workshop’s end, attendees gain proficiency in crucial Digital Image Processing techniques, empowering them to address challenges in diverse industries. Join us to elevate your understanding and application of image processing in this dynamic and engaging training program.

Learning Objectives:

  • Understand fundamental concepts of Digital Image Processing.
  • Acquire hands-on experience with image enhancement techniques.
  • Master image filtering and convolution operations.
  • Explore advanced image segmentation and feature extraction methods.
  • Develop proficiency in image restoration and denoising.
  • Gain insights into image compression and coding techniques.
  • Apply machine learning algorithms for image recognition.
  • Analyze real-world applications of Digital Image Processing.

Audience: This workshop is tailored for professionals and enthusiasts in fields such as computer vision, photography, biomedical imaging, and multimedia. It is suitable for engineers, researchers, and practitioners seeking to deepen their understanding and application of Digital Image Processing techniques.

Course Outline:

Introduction to Digital Image Processing (DIP)

    • Overview of image representation
    • Basic concepts and terminologies
    • Image acquisition and digitization

Image Enhancement Techniques

    • Histogram equalization
    • Contrast stretching
    • Spatial domain methods
    • Frequency domain methods

Image Filtering and Convolution Operations

    • Convolution and correlation
    • Linear and non-linear filtering
    • Edge detection and sharpening filters
    • Morphological operations

Image Segmentation and Feature Extraction

    • Thresholding techniques
    • Region-based segmentation
    • Feature extraction methods
    • Texture analysis

Image Restoration and Denoising

    • Degradation models
    • Inverse filtering
    • Wiener filtering
    • Non-local means denoising

Image Compression and Coding Techniques

    • Lossless and lossy compression
    • Transform coding (e.g., DCT)
    • JPEG and JPEG2000 standards
    • Wavelet-based compression

Machine Learning for Image Recognition

    • Introduction to machine learning in DIP
    • Supervised and unsupervised learning
    • Convolutional Neural Networks (CNNs)
    • Transfer learning for image recognition

Real-World Applications of Digital Image Processing

    • Medical image processing
    • Satellite image analysis
    • Object recognition in computer vision
    • Image processing in multimedia

Participants will leave the workshop with a robust skill set in Digital Image Processing, ready to apply their knowledge to diverse industry challenges.

 

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