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Image Segmentation (Chapter 10). CSC 446 Lecturer: Nada ALZaben. Introduction. Segmentation subdivides an image into its constituent regions or objects. The level of subdivision is done depending on the level where we isolate the object of interest in the application from the background.
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Image Segmentation(Chapter 10) CSC 446 Lecturer: Nada ALZaben
Introduction • Segmentation subdivides an image into its constituent regions or objects. • The level of subdivision is done depending on the level where we isolate the object of interest in the application from the background. • Segmentation is a preprocessing algorithm for feature extraction.
Segmentation Techniques • Detection of discontinuities • Point detection • Line detection • Edge detection • Detection of similarities.
Detection of discontinuities • Will apply the mask 3X3 on image and get R: R=w1z1+w2z2+……+w9z9 • Point detection: we detect isolated points where
Detection of discontinuities • Line detection: we detect lines by computing R1,R2,R3 and R4 using the 4 masks
Detection of discontinuities • Edge detection: it contains horizontal and vertical edge estimates and
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Representation and Description (Chapter 11) CSC 446 Lecturer: Nada ALZaben
Introduction • The data resulted from segmentation need to be represented and described in a way that can be processed in another step. • Representing a region can be in 2 ways: • In term of its boundary's. • In term of its internal characteristics. • After representing the data it needs to be described either by its length, area,….etc.
Representation (Chain Code) • Chain code are used to represent a boundary by a connected square of straight line segments of specific length and direction. • It is based on 4 or 8 connectivity of the segments. • The direction of each segment is coded using number schema.
Chain Code • Disadvantages: • The result chain code is long • If the boundary has some disturbance cause changes in the chain code • Solution use grid.
Chain Code Example 1 Input: 446567001232
Object Recognition (Chapter 12) CSC 446 Lecturer: Nada ALZaben
Pattern Recognition System • A pattern recognition system is composed of • Pre-processing • Feature extraction (very important) • Classification Input image Scanning and data capture Preprocessing segmentation Feature extraction Classes Classification