A Contour Shape Description Method Via Transformation to Rotation and Scale Invariant Coordinates System

2006 ◽  
pp. 312-322 ◽  
Author(s):  
Min-Ki Kim
Keyword(s):  
Shape Description ◽  
Scale Invariant ◽  
Contour Shape

Long-distance deformation object recognition by integrating contour structure and scale-invariant heat kernel signature

2020 ◽  
Vol 39 (3) ◽  
pp. 3241-3257
Author(s):  
Xinggui Xu ◽  
Ping Yang ◽  
Bing Ran ◽  
Hao Xian ◽  
Yong Liu
Keyword(s):  
Object Recognition ◽  
Heat Kernel ◽  
Critical Points ◽  
Feature Fusion ◽  
Real Life ◽  
Local Deformation ◽  
Scale Invariant ◽  
Long Distance ◽  
Contour Shape ◽  
Heat Kernel Signature

The tough challenges of object recognition in long-distance scene involves contour shape deformation invariant features construction. In this work, an effective contour shape descriptor integrating critical points structure and Scale-invariant Heat Kernel Signature (SI-HKS) is proposed for long-distance object recognition. We firstly propose a general feature fusion model. Then, we capture the object contour structure feature with Critical-points Inner-distance Shape Context (CP-IDSC). Meanwhile, we pull-in the SI-HKS for capturing the local deformation-invariant properties of 2D shape. Based on the integration of the above two feature descriptors, the fusion descriptor is compacted by mapping into a low dimensional subspace using the bags-of-features, allowing for an efficient Bayesian classifier recognition. The extensive experiments on synthetic turbulence-degraded shapes and real-life infrared image show that the proposed method outperformed other compared approaches in terms of the recognition precision and robustness.

Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape

2001 ◽  
Vol 13 (8) ◽  
pp. 1683-1711 ◽  
Author(s):  
Lance R. Williams ◽  
Karvel K. Thornber
Keyword(s):  
Illusory Contour ◽  
Neural Model ◽  
Constant Speed ◽  
Invariant Distribution ◽  
Emergent Properties ◽  
Scale Invariant ◽  
Brownian Motions ◽  
Contour Shape ◽  
Orientation Scale

A recent neural model of illusory contour formation is based on a distribution of natural shapes traced by particles moving with constant speed in directions given by Brownian motions. The input to that model consists of pairs of position and direction constraints, and the output consists of the distribution of contours joining all such pairs. In general, these contours will not be closed, and their distribution will not be scaleinvariant. In this article, we show how to compute a scale-invariant distribution of closed contours given position constraints alone and use this result to explain a well-known illusory contour effect.

scholarly journals Local feature extraction of sheepskin based on structure contour shape description

2021 ◽  
Vol 336 ◽  
pp. 06026
Author(s):  
Lianhua Hu ◽  
Chengyi Xiang ◽  
Feng Zhang
Keyword(s):  
Computer Vision ◽  
Feature Extraction ◽  
Experimental Simulation ◽  
Shape Description ◽  
Contour Shape ◽  
Edge Removal ◽  
Starting Point ◽  
Computer Vision Technology ◽  
Local Feature Extraction ◽  
Implementation Steps

Based on the precise sheepskin contour extracted by computer vision technology in the previous research of the team, this paper proposes the shape description technology based on the structure contour to extract the local features of the sheepskin, such as the head and hooves and the waste edge, which is the basis for the automatic edge removal of the sheepskin in the future. The algorithm uses Angle and position relation to segment the precise contour track of raw sheepskin into graph elements, and then uses geometric parameter shape description operator to describe and extract the edges that need to be removed, so as to obtain the starting point and end point of each local contour that needs to be removed. In this paper, the principle and implementation steps of this method are introduced in detail, and the experimental simulation verification shows that the extraction effect is good, which can meet the requirements of subsequent industrial production of automatic sheepskin cutting.

Contour shape description based on an arch height function

1992 ◽  
Vol 25 (1) ◽  
pp. 17-23 ◽  
Author(s):  
Yijia Lin ◽  
Jiqing Dou ◽  
Hongmei Wang
Keyword(s):  
Height Function ◽  
Shape Description ◽  
Arch Height ◽  
Contour Shape

Mathematical morphology for shape description

2002 ◽  
Vol 12 (1) ◽  
pp. 87-116 ◽  
Author(s):  
M. Schmitt
Keyword(s):  
Mathematical Morphology ◽  
Shape Description

Hybrid G-PRNU: Optimal parameter selection for scale-invariant asymmetric source smartphone identification

2019 ◽  
Vol 2019 (5) ◽  
pp. 546-1-546-7 ◽  
Author(s):  
Reepjyoti DEKA ◽  
Chiara GALDI ◽  
Jean-Luc DUGELAY
Keyword(s):  
Optimal Parameter ◽  
Parameter Selection ◽  
Scale Invariant ◽  
Selection For ◽  
Optimal Parameter Selection
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