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'Tree'에 해당되는 글 2건

2010.09.03 OpenCV: cvFindContours( )
2009.06.11 Sahni's ch.16 Graphs

OpenCV: cvFindContours( )

2010. 9. 3. 16:23 Computer Vision/2010ETRI-MultiAutoCalib

OpenCV: cvFindContours( )

cvFindContours()

int cvFindContours(CvArr* image, CvMemStorage* storage, CvSeq** first_contour, int header_size=sizeof(CvContour), int mode=CV_RETR_LIST, int method=CV_CHAIN_APPROX_SIMPLE, CvPoint offset=cvPoint(0, 0))¶

Finds the contours in a binary image.

Parameters:

Parameters:	image – The source, an 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - the image is treated as `binary` . To get such a binary image from grayscale, one may use Threshold , AdaptiveThreshold or Canny . The function modifies the source image’s content storage – Container of the retrieved contours first_contour – Output parameter, will contain the pointer to the first outer contour header_size – Size of the sequence header, $\ge \texttt{sizeof(CvChain)}$ if $\texttt{method} =\texttt{CV\_CHAIN\_CODE}$ , and $\ge \texttt{sizeof(CvContour)}$ otherwise mode – Retrieval mode CV_RETR_EXTERNAL retrives only the extreme outer contours CV_RETR_LIST retrieves all of the contours and puts them in the list CV_RETR_CCOMP retrieves all of the contours and organizes them into a two-level hierarchy: on the top level are the external boundaries of the components, on the second level are the boundaries of the holes CV_RETR_TREE retrieves all of the contours and reconstructs the full hierarchy of nested contours method – Approximation method (for all the modes, except `CV_LINK_RUNS` , which uses built-in approximation) CV_CHAIN_CODE outputs contours in the Freeman chain code. All other methods output polygons (sequences of vertices) CV_CHAIN_APPROX_NONE translates all of the points from the chain code into points CV_CHAIN_APPROX_SIMPLE compresses horizontal, vertical, and diagonal segments and leaves only their end points CV_CHAIN_APPROX_TC89_L1,CV_CHAIN_APPROX_TC89_KCOS applies one of the flavors of the Teh-Chin chain approximation algorithm. CV_LINK_RUNS uses a completely different contour retrieval algorithm by linking horizontal segments of 1’s. Only the `CV_RETR_LIST` retrieval mode can be used with this method. offset – Offset, by which every contour point is shifted. This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context

image – The source, an 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - the image is treated as binary . To get such a binary image from grayscale, one may use Threshold , AdaptiveThreshold or Canny . The function modifies the source image’s content
storage – Container of the retrieved contours
first_contour – Output parameter, will contain the pointer to the first outer contour
header_size – Size of the sequence header, $\ge \texttt{sizeof(CvChain)}$ if $\texttt{method} =\texttt{CV\_CHAIN\_CODE}$ , and $\ge \texttt{sizeof(CvContour)}$ otherwise
mode –
Retrieval mode
- CV_RETR_EXTERNAL retrives only the extreme outer contours
- CV_RETR_LIST retrieves all of the contours and puts them in the list
- CV_RETR_CCOMP retrieves all of the contours and organizes them into a two-level hierarchy: on the top level are the external boundaries of the components, on the second level are the boundaries of the holes
- CV_RETR_TREE retrieves all of the contours and reconstructs the full hierarchy of nested contours
method –
Approximation method (for all the modes, except CV_LINK_RUNS , which uses built-in approximation)
- CV_CHAIN_CODE outputs contours in the Freeman chain code. All other methods output polygons (sequences of vertices)
- CV_CHAIN_APPROX_NONE translates all of the points from the chain code into points
- CV_CHAIN_APPROX_SIMPLE compresses horizontal, vertical, and diagonal segments and leaves only their end points
- CV_CHAIN_APPROX_TC89_L1,CV_CHAIN_APPROX_TC89_KCOS applies one of the flavors of the Teh-Chin chain approximation algorithm.
- CV_LINK_RUNS uses a completely different contour retrieval algorithm by linking horizontal segments of 1’s. Only the CV_RETR_LIST retrieval mode can be used with this method.
offset – Offset, by which every contour point is shifted. This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context

Learning OpenCV: Chater 8. Contours: Contour Finding
: 234p
"the concept of a contour tree"

Suzuki, M. (1985) Evapotranspiration Estimates of Forested Watersheds in Japan Using the Short-time Period Water-budget Methods. Journal of Japanese Forest Society, 67: 115-125. (in Japanese with English summary)

저작자표시 비영리 동일조건

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posted by maetel

Sahni's ch.16 Graphs

2009. 6. 11. 20:36 @GSMC/서용덕: Multimedia Programming C++

Sahni
Data Structures, Algorithms and Applications in C++, 2nd ed.
: Chapter 16 Graphs

graph data structure

terminology:
vertex, edge, adjacent, incident, degree, cycle, path, connected component, and spanning tree

types:
undirected / directed / weighted

representation:
adjacent matrix / array adjacency lists / linked adjacency lists

standard graph search methods:
breadth-first / depth-first search

algorithms:

16.1 Definitions

graph
: an ordered pair of finite sets of vertices (or nodes or points) and edges (or arcs or lines)

http://en.wikipedia.org/wiki/Graph_(data_structure )

loop
: self-edge

digraph
: directed graph

network
: weighted undirected graph or digraph

16.2 Applications and More Definitions

example 16.1: path problems

example 16.2: spanning trees

A graph is connected iff there is a path between every pair of vertices in the graph.

cycle
: simiple path with the same start and end vertex

tree
: a connected undirected graph that contains no cycles

spanning tree
: a subgraph of a graph that contains all the vertices of the graph and is a tree

example 16.3: interpreters

bipartite graphs

16.3 Properties

http://en.wikipedia.org/wiki/List_of_graph_theory_topics

in-degree
out-degree

complete digraph

16.4 The ADT graph

ADT graph = Abstract Data type graph

http://en.wikipedia.org/wiki/Abstract_data_type

http://en.wikipedia.org/wiki/Pure_virtual_method

16.5 Representation of Unweighted Graphs

adjacency matrix
linked adjacency list
array adjacency list

http://en.wikipedia.org/wiki/Adjacency_matrix

http://en.wikipedia.org/wiki/Adjacency_list

http://en.wikipedia.org/wiki/Graph_theory

16.6 Representation of Weighted Graphs

cost-adjacency-matrix

16.7 Class Implementations

16.8 Graph Search Methods

Breadth-First Search (BFS)
http://en.wikipedia.org/wiki/Breadth_first_search

queue
http://cplusplus.com/reference/stl/queue/
http://en.wikipedia.org/wiki/Queue_(data_structure)

cf. stack
http://cplusplus.com/reference/stl/stack/

list
http://cplusplus.com/reference/stl/list/

cp. level-order traversal of a binary tree
http://en.wikipedia.org/wiki/Binary_search_tree#Traversal

Depth-First Search (DFS)
http://en.wikipedia.org/wiki/Depth-first_search

cp. pre-order traversal of a binary tree

http://en.wikipedia.org/wiki/Dijkstra%27s_algorithm

http://en.wikipedia.org/wiki/Floyd%E2%80%93Warshall_algorithm

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Deitel <C++ How to program> Sixth ed. (0)	2009.03.07

posted by maetel

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