complex networks for representation and characterization of object
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Complex Networks for Representation and Characterization of Object. For CS790g Project Bingdong Li 11/9/2009. Outline Of Methodology. Re-introduce Traditional Approaches Proposed Methods Issues Summary Questions and Comments. Re-introduce Traditional Approaches . - PowerPoint PPT PresentationTRANSCRIPT
Complex Networks for Representation and
Characterization of Object
For CS790g ProjectBingdong Li11/9/2009
Outline Of Methodology• Re-introduce Traditional Approaches • Proposed Methods• Issues• Summary• Questions and Comments
Re-introduce Traditional Approaches
• External characteristics:– boundary and shape– chain codes, polygonal approximations, skeletons
• Internal characteristics:– color and texture, – statistical approaches, structural approaches,
spectral approaches• Both external and internal characteristics.
Source: CS674 Image Processing Lecture
Proposed Methods:Representation
• Define the network– a regular lattice network in 2-D background, each
node is connected to its nearest neighbors depending on the Euclidean distance
– Each node is addressed by its normalized degree
Source: CS674 Image Processing Lecture
Proposed Methods:Representation
• Two pixel A and B on the contourA <-->B <==> d(A, B) <= r and d(A, B) >= n
– r is the shape control threshold– n is noise control threshold– d is the normalized distance– k is the average degree
From Raw Image
To Matrices
Proposed Methods:Representation
Proposed Methods:Characterization
• Network similarity algorithm: structural similarities
Mehler, Alexander(2008) 'STRUCTURAL SIMILARITIES OF COMPLEX NETWORKS: A COMPUTATIONAL MODEL BY EXAMPLE OF WIKI GRAPHS',Applied Artificial Intelligence,22:7,619 — 683
Algorithm
1. Raw image2. Segmentation3. Build the complex network4. Classifying the object using network similarity
algorithm
Expected Results
• In most case, it will be a small world network
Expected Results
• A methods for object classification that– Leverage complex network technology– Represent the geometric information– Represent the spatial information– Invariant to rotation– Invariant to translation
Issues
• the photometric information was not represented
• Thresholds
Summary
• In this project, we tried a new approach for representation and characterization of object
• Firstly, traditional approaches and complex network related approaches are reviewed
• Then, proposed a new methods, its definition of network, characterization, and algorithm to classify an object
Questions and Comments
Thanks