Outline Announcement Perceptual organization, grouping, and segmentation Hough transform Read Chapter 17 of the textbook File: week14-m.ppt.

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Presentation transcript:

Outline Announcement Perceptual organization, grouping, and segmentation Hough transform Read Chapter 17 of the textbook File: week14-m.ppt

Visual Perception Modeling Announcement Class evaluation this coming Friday Please come to class on time so that we can start the class evaluation first Class presentation Your presentation should be about 20 minutes following a brief question-and-answer section which is about 5 minutes 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Introduction – cont. Computational models/implementations There are generally two kinds of computational models/implementations for segmentation Based on homogeneity measure to group pixels with similar attributes together Region growing/split-and-merge Based on discontinuity of attributes to detect boundaries/contours of regions Active contours 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Introduction – cont. Hough transform An algorithm to group edge points from edge detectors or from any other process 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform Straight line case Consider a single isolated edge point (xi, yi) There are an infinite number of lines that could pass through the points Each of these lines can be characterized by some particular equation 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. Hough transform algorithm 1. Find all of the desired feature points in the image 2. For each feature point For each possibility i in the accumulator that passes through the feature point Increment that position in the accumulator 3. Find local maxima in the accumulator 4. If desired, map each maximum in the accumulator back to image space 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. A better way of expressing lines for hough transform 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. Circles Hough transform can also be used for circles 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. Here the radius is fixed 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. A 3-dimensional parameter space for circles in general 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. More complicated shapes As you can see, the hough transform can be used to find shapes with arbitrary complexity as long as we can describe the shape with some fixed number of parameters The number of parameters required indicates the dimensionality of the accumulator 4/6/2019 Visual Perception Modeling

Generalized Hough Transform Some shapes may not be easily expressed using a small set of parameters In this case, we explicitly list all the points on the shape This variation of Hough transform is known as generalized Hough transform 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. Implementation issues Quantization of the accumulator space Utilization of additional information For line-matching Hough transform, the orientation of an edge point from the Canny edge detector can be used to limit the votes in the accumulator space Smoothing the accumulator To reduce the effects of noise Gray-level voting 4/6/2019 Visual Perception Modeling

Visual Perception Modeling Hough Transform – cont. Implementation issues - continued Refining the accumulator Find a maximum and vote only near the maximum with a higher resolution of the parameter space Randomized Hough transform 4/6/2019 Visual Perception Modeling