Image Processing with MATLAB

Day 1 of 2

Importing and Visualizing Images

Objective: Import and visualize different image types in MATLAB. Manipulate images for streamlining subsequent analysis steps.

• Importing, inspecting, and displaying images
• Converting between image types
• Visualizing results of processing
• Exporting images

Preprocessing Images

Objective: Enhance images for analysis by using common preprocessing techniques such as contrast adjustment and noise filtering.

• Adjusting contrast
• Reducing noise with spatial filtering
• Equalizing inhomogeneous background
• Processing images in distinct blocks
• Measuring image quality

Color and Texture Segmentation

Objective: Segment objects from an image based on color and texture. Use statistical measures to characterize texture features and measure texture similarity between images.

• Transforming between image color spaces
• Segmenting objects based on color attributes and color difference
• Segmenting objects based on texture using nonlinear filters
• Analyzing image texture using statistical measures like contrast and correlation

Improving Segmentation

Objective: Improve binary segmentation results by refining the segmentation mask. Use interactive and iterative techniques to segment image regions.

• Using morphological operations to refine segmentation masks
• Segmenting images and refining results interactively
• Using iterative techniques to evolve segmentation from a seed

Day 2 of 2

Finding and Analyzing Objects

Objective: Count and label objects detected in a segmentation. Measure object properties like area, perimeter, and centroids.

• Extracting and labeling objects in a segmentation mask
• Measuring shape properties
• Separating adjacent and overlapping objects with watershed transform

Detecting Edges and Shapes

Objective: Detect edges of objects and extract boundary pixel locations. Detect objects by shapes such as lines and circles.

• Detecting object edges
• Identifying objects by detecting lines and circles
• Performing batch analysis over sets of images

Spatial Transformation and Image Registration

Objective: Compare images with different scales and orientations by geometrically aligning them.

• Applying geometric transformations to images
• Aligning images using phase correlation
• Aligning images using point mapping

Automating Image Registration with Image Features

Objective: Detect, extract, and match sets of image features to automate image registration.

• Detecting and extracting features
• Matching features to estimate geometric transformation between two images