'Edge relaxation' presentation slideshows

Segmentation

801 views • 54 slides

Computer Vision

513 views • 36 slides

Shortest Paths

0. A. 4. 8. 2. 8. 2. 3. 7. 1. B. C. D. 3. 9. 5. 8. 2. 5. E. F. Shortest Paths. Weighted Graphs. In a weighted graph, each edge has an associated numerical value, called the weight of the edge Edge weights may represent, distances, costs, etc. Example:

272 views • 26 slides

Graphs

Graphs. 1843. ORD. SFO. 802. 1743. 337. 1233. LAX. DFW. Many slides taken from Goodrich, Tamassia 2004. A graph is a pair ( V, E ) , where V is a set of nodes, called vertices (node=vertex) E is a collection of pairs of vertices, called edges

443 views • 23 slides

Edge Based Segmentation

Edge Based Segmentation. Xinyu Chang. Outline. Introduction Canny Edge detector Edge Relaxation Border Tracing. Introduction.

378 views • 20 slides

Canny Edge Detector

Canny Edge Detector. However, usually there will still be noise in the array E[i, j], i.e., non-zero values that do not correspond to any edge in the original image. In most cases, these values will be smaller than those indicating actual edges.

462 views • 17 slides

Weighted Graphs

Weighted Graphs. In a weighted graph, each edge has an associated numerical value, called the weight of the edge Edge weights may represent, distances, costs, etc. Example: In a flight route graph, the weight of an edge represents the distance in miles between the endpoint airports. 849.

1.98k views • 12 slides

Query Relaxation for XML Database

Query Relaxation for XML Database. Award #: 0219442 PI: Wesley W. Chu Computer Science Dept. UCLA. Problem Overview. Goal Develop an XML query relaxation framework for searching answers that can approximately match the given query conditions. Query Relaxation

182 views • 4 slides