Exploring Image Segmentation

In this presentation, we'll dive into different techniques for image segmentation and highlight their unique uses. Get ready to experience the world of image processing!

Thresholding: A simple yet powerful segmentation technique

Thresholding is a basic segmentation technique that partitions an image into two regions - foreground and background. Various techniques such as global, adaptive, and Otsu can be used. Learn about the applications and usage of thresholding in the following examples:

Application of thresholding in medical imaging

Thresholding is used for detecting tumor regions in mammography images.

Application of thresholding in traffic monitoring

Thresholding is used for vehicle detection and tracking in low visibility scenarios.

Application of thresholding in food industry

Thresholding is used to detect defects and quality checking in food production.

Splitting and Merging: A simple approach to partitioning an image

Segmentation by splitting and merging is an iterative process of dividing the image into smaller regions based on a similarity criterion and then merging them into larger segments. It's a great approach for images with similar regions. Here are some examples:

Image Compression

Splitting an image into smaller segments reduces the image size and can be used for efficient compression.

Object Recognition

Splitting an image into smaller segments based on texture, shape or color can be used to recognize objects in the image.

Semantic Segmentation in Satellite Imagery

Merging smaller regions into larger ones is useful for providing a semantic context to satellite imagery.

Segmentation by Morphological Watersheds: A powerful technique for image segmentation

Morphological watershed is a powerful technique that partitions the image into regions by defining contours. The technique allows for segmenting the image based on texture and color. Here are some examples:

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Medical Applications

Finding tumor regions in Magnetic Resonance Imaging is one of the important medical applications of morphological watersheds.

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Industrial Applications

Morphological watershed algorithm is used for segmenting industrial images in the electronics and steel industry.

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Image Processing Applications

Morphological watershed transform is used for image segmentation in applications like fingerprint analysis and remote sensing.

Introduction to motion-based segmentation

This section will highlight the process of segmenting an image based on motion. The following items discuss the basic and advanced techniques used in the process:

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Basic Techniques

Includes background subtraction, frame differencing, and optical flow.

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Advanced Techniques

Includes mean-shift tracking, active contours, and graph cut-based segmentation.

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Application Examples

Motion-based segmentation is used in applications like traffic analysis, surveillance, and object tracking.

Basic motion estimation techniques

Motion estimation is the process of detecting changes in the position of an object in consecutive frames. Here are some basic motion estimation techniques:

Block-Based Motion Estimation

Dividing the image into blocks and comparing them between frames makes this method useful for video compression.

Optical Flow Technique

Optical flow provides the displacement field between consecutive frames, useful in applications like tracking and action detection.

Phase Correlation

Phase correlation is used for aligning images and is useful in applications like panoramic stitching and background subtraction.

Advanced motion estimation techniques

Advanced techniques are utilized when basic techniques fall short. Here are some advanced techniques with their respective applications:

Applications of motion-based segmentation

Motion-based segmentation is applied extensively in various fields - from traffic analysis to medical imaging. Use of motion-based segmentation can assist in more efficient and detailed studies. Check out some examples:

Application in Sports Analysis

Motion-based segmentation finds application in sports analytics, such as determining players' movements on the field.

Application in Surveillance

Motion-based segmentation finds use in monitoring group activity and behavior, such as crowd surveillance.

Application in Medical Imaging

Motion-based segmentation helps in identifying, monitoring, and diagnosing diseases using medical imaging.