scholarly journals 3D mesh skeleton extraction using prominent segmentation

2010 ◽  
Vol 7 (1) ◽  
pp. 63-74
Author(s):  
Xiaopeng Sun ◽  
J. Pan ◽  
Xiaopeng Wei
Keyword(s):  
Shape Description ◽  
Feature Points ◽  
Shape Feature ◽  
Skeleton Extraction ◽  
Geometry Processing ◽  
3D Mesh ◽  
Principal Curve ◽  
Digital Geometry Processing ◽  
Extraction Algorithm ◽  
Core Extraction

Skeleton of 3D mesh is a fundamental shape feature, and is useful for shape description and other many applications in 3D Digital Geometry Processing. This paper presents a novel skeleton extraction algorithm based on feature point and core extraction by the Multidimensional scaling (MDS) transformation. The algorithm first straights the folded prominent branch up, as well as the prominent shape feature points of mesh are computed, a meaningful segmentation is applied under the direction of feature points. The Node-ring of all segmented components is defined by discrete geodesic path on mesh surface, and then the skeleton of every segmented component is defined as the link of the Node-ring's center. As to the core component without prominent feature points, principal curve is used to fit its skeleton. Our algorithm is simple, and invariant both to the pose of the mesh and to the different proportions of model's components.

scholarly journals 3D Mesh Pre-processing Method Based on Feature Point Classification and Anisotropic Vertex Denoising Considering Scene Structure Characteristics

2021 ◽  
Vol 13 (11) ◽  
pp. 2145
Author(s):  
Yawen Liu ◽  
Bingxuan Guo ◽  
Xiongwu Xiao ◽  
Wei Qiu
Keyword(s):  
Real Data ◽  
Geometric Constraints ◽  
Feature Point ◽  
Feature Points ◽  
Denoising Method ◽  
3D Mesh ◽  
Mesh Denoising ◽  
Scene Structure ◽  
Sharp Edges ◽  
Update Strategy

3D mesh denoising plays an important role in 3D model pre-processing and repair. A fundamental challenge in the mesh denoising process is to accurately extract features from the noise and to preserve and restore the scene structure features of the model. In this paper, we propose a novel feature-preserving mesh denoising method, which was based on robust guidance normal estimation, accurate feature point extraction and an anisotropic vertex denoising strategy. The methodology of the proposed approach is as follows: (1) The dual weight function that takes into account the angle characteristics is used to estimate the guidance normals of the surface, which improved the reliability of the joint bilateral filtering algorithm and avoids losing the corner structures; (2) The filtered facet normal is used to classify the feature points based on the normal voting tensor (NVT) method, which raised the accuracy and integrity of feature classification for the noisy model; (3) The anisotropic vertex update strategy is used in triangular mesh denoising: updating the non-feature points with isotropic neighborhood normals, which effectively suppressed the sharp edges from being smoothed; updating the feature points based on local geometric constraints, which preserved and restored the features while avoided sharp pseudo features. The detailed quantitative and qualitative analyses conducted on synthetic and real data show that our method can remove the noise of various mesh models and retain or restore the edge and corner features of the model without generating pseudo features.

scholarly journals A Development Perspective of Point-Based Computer Graphics

2021 ◽  
Vol 39 (2) ◽  
pp. 343-352
Author(s):  
Ajahati Mukti
Keyword(s):  
Computer Graphics ◽  
Rapid Development ◽  
Three Dimensional ◽  
Sampled Data ◽  
Geometry Processing ◽  
Digital Geometry Processing ◽  
Physical Interactions ◽  
Key Techniques ◽  
Future Work ◽  
Development Perspective

Every object has its characteristic shape, appearance and responses to physical interactions. Computer graphics center on those three components of an object to bring them onto the computer display. With the rapid development of three dimensional (3D) printing technology, the accuracy of the focused object’s geometry was put forward. Point-based graphing is a way to taking the role in rendering the huge 3D sampled data. Based on the digital geometry processing of point-sampled model, various algorithms were reviewed, and some related key techniques were compared with the potential perspective of the future work in this area was also presented．

scholarly journals Handwritten tifinagh character recognition using simple geometric shapes and graphs

2019 ◽  
Vol 13 (2) ◽  
pp. 598
Author(s):  
Youssef Ouadid ◽  
Abderrahmane Elbalaoui ◽  
Mehdi Boutaounte ◽  
Mohamed Fakir ◽  
Brahim Minaoui
Keyword(s):  
Character Recognition ◽  
Graph Matching ◽  
Recognition Rate ◽  
Recognition System ◽  
Features Extraction ◽  
Experimental Results ◽  
Feature Points ◽  
Matching Method ◽  
Extraction Algorithm ◽  
Novel Algorithm

<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

A Novel Skeleton Extraction Algorithm in Sensor Networks

2014 ◽  
pp. 27-35 ◽  
Author(s):  
DongHui Zhu ◽  
Yubao Wang ◽  
Jing Xing ◽  
Wenping Liu ◽  
Hongbo Jiang ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Skeleton Extraction ◽  
Extraction Algorithm

scholarly journals An Integrated Technique for Image Forgery Detection using Block and Keypoint Based Feature Techniques

2018 ◽  
Vol 7 (3.12) ◽  
pp. 505 ◽  
Author(s):  
Leela Apurupa ◽  
J D.Dorathi Jayaseeli ◽  
D Malathi
Keyword(s):  
Human Life ◽  
Image Process ◽  
Feature Points ◽  
Forgery Detection ◽  
Digital Image Process ◽  
Satellite Imaging ◽  
Extraction Algorithm ◽  
Region Extraction ◽  
Integrated Technique ◽  
Algorithmic Rule

The invention of the net has introduced the unthinkable growth and developments within the illustrious analysis fields like drugs, satellite imaging, image process, security, biometrics, and genetic science. The algorithms enforced within the twenty first century has created the human life more leisurely and secure, however the protection to the first documents belongs to the genuine person is remained as involved within the digital image process domain. a replacement study is planned during this analysis paper to discover. The key plan in the deliberate take a look at and therefore the detection of the suspected regions are detected via the adaptive non-overlapping and abnormal blocks and this method is allotted exploitation the adaptive over-segmentation algorithmic rule. The extraction of the feature points is performed by playacting the matching between every block and its options. The feature points are step by step replaced by exploitation the super pixels within the planned Forgery Region Extraction algorithm then merge the neighboring obstructs that have comparative local shading decisions into the element squares to encourage the brought together districts; at last, it applies the morphological activity to the bound together areas to ask the recognized falsification districts The planned forgery detection algorithmic rule achieves far better detection results even below numerous difficult conditions the sooner strategies all told aspects. We have analyzed the results obtained by the each SIFT and SURF and it is well-tried that the planned technique SURF is giving more satisfactory results by both subjective and objective analysis.  

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