Objective: Import images into MATLAB and visualize them. Convert the images to a format that is useful for subsequent analysis steps.

• Importing and displaying images
• Converting between image types
• Exporting images

Objective: Interactively explore object details such as size and color to find start values for subsequent image processing steps. To apply the steps repeatedly, you can create custom image exploration tools from the interactive modules.

• Obtaining pixel intensity values
• Extracting a region of interest (ROI)
• Computing pixel statistics on a region of interest
• Measuring object sizes
• Creating a custom interactive tool

Objective: Preprocess images by filtering, and using contrast adjustment to simplify or allow for image analysis steps.

• Adjusting image contrast
• Reducing noise in an image by filtering
• Handling inhomogenous background
• Applying custom functions block by block

Objective: Compare images with different scaling and orientation by aligning them. Use the same techniques for creating panorama images.

• Geometric transformations
• Image registration using point mapping
• Creating a panoramic scene

Objective: Segment edges of objects and extract boundary pixel locations. Detect lines and circles in an image.

• Segmenting object edges
• Detecting straight lines
• Performing batch analysis over sets of images
• Detecting circular objects

Objective: Segment objects based on color or texture. Use texture features for image classification.

• Color space transformation
• Color segmentation
• Texture segmentation
• Texture-based image classification

Objective: Analyze and modify the objects' shape to improve segmentation results. Count the detected objects and calculate object features like area or centroids.

• Counting objects
• Measuring shape properties
• Using morphological operations
• Performing watershed segmentation