10 Questions
What is the simplest chain code mechanism also known as?
Crack code
What is the purpose of allocating numbers based on directions in chain code?
To reduce the boundary of an object to a sequence of numbers
What is the first step in constructing a chain code?
Select some starting point of the boundary and represent it by its absolute coordinates
What is an advantage of chain code?
It provides good compression of boundary description
What is a problem with chain code?
It has long chains of codes
What is a solution to the problem of chain code being sensitive to noise?
Re-sample the image to a lower resolution
What is a limitation of chain code?
It has no invariance to Rotation and Scale
What is a problem with chain code sequence?
It depends on a starting point
What do the numbers in the chain code represent?
Directions followed by the bug tracking algorithm
What is the purpose of the bug tracking algorithm in chain code?
To allocate numbers based on directions
Study Notes
Feature Recognition and Classification
- Feature recognition is necessary to reduce the dimensionality of the classification task by measuring essential properties or features of objects.
Features
- Features are higher-level representations of structure and shape.
- Features should be chosen to preserve the information that is important to the particular task at hand.
- Two categories of features:
- Describing the contents of objects (e.g., mean pixel value, standard deviation, contrast, entropy, texture)
- Describing the shape of objects (e.g., size, perimeter, circularity, skeleton, Euler number)
Image Representation and Feature Extraction
- Representation makes object information more accessible for computer-interpretation.
- Description quantifies the representation of the object.
- Feature extraction detects and represents features of interest within an image for further processing.
Why Features?
- Features are used for diagnosis, radiation therapy, and multi-modality registration of images.
- Features are extracted to identify treatment areas and boundaries.
Features Characteristics
- Features should be:
- Robust (invariant to translation, orientation, scale, and illumination)
- Discriminating (different values for objects in different classes)
- Reliable (similar values for objects of the same class)
- Independent (uncorrelated features)
- Simple to extract for large-scale screening.
Feature Vector
- A feature vector or pattern vector contains the measured features for a particular object or region.
- The feature space is n-dimensional, with each feature constituting a dimension.
- In classification, the goal is to assign each feature vector to one of a set of classes.
Types of Representation
- Two types of representation:
- Boundary (External characteristics)
- Region (Internal characteristics)
Boundary Descriptors Techniques
- Chain Code:
- A boundary representation technique that represents a contour as a sequence of straight line segments of specified length and direction.
- The simplest chain code mechanism allocates numbers based on directions, reducing the boundary of an object to a sequence of numbers.
- Chain code provides good compression of boundary description but is sensitive to noise and not rotation and scale invariant.
This quiz covers the concepts of feature recognition and classification in medical imaging, including pre-processing and dimensionality reduction. It is based on Lecture 6 of a medical imaging course.
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