Gray Level Topological Angle Detection of High Curvature Points

Date

2010-07-07

Author

Cihan, Ibrahim Kivanc
ŞENEL, HAKAN GÜRAY

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

256
views

0
downloads

A new method of angle detection based on the topological median filter is proposed. Topological opening operator is used to detect corners and Topological closing operator is used to calculate the corner angles on gray level images.

Subject Keywords

Corner detection

URI

https://hdl.handle.net/11511/65335

Conference Name

IEEE International Symposium on Industrial Electronics (ISIE)

Collections

Unclassified, Conference / Seminar

Suggestions

OpenMETU
Core

Gray level topological corner detection Cihan, Ibrahim Kivanc; Senel, Hakan Gueray (2007-06-07) A new corner detection algorithm based on the topological median filter is proposed. Topological quasi dilation and erosion operators with circular structuring element are used to detect the corners on gray level images.
Topological Navigation Algorithm Design and Analysis Using Spherical Images Şahin, Yasin; Koku, Ahmet Buğra; Department of Mechanical Engineering (2022-8-23) A topological navigation algorithm that has the capability of mapping and localization based on visual contents is proposed. Keypoint detection and feature matching are conducted on spherical images to extract significant features among sequential frames. Robot movement direction is estimated based on historical angle differences of significant features to reach the final destination. The navigation process is supported with visual egocentric localization to gain simultaneous localization and mapping compet...
Marginalized particle filters for Bayesian estimation of Gaussian noise parameters Zhao, Yuxin; Yin, Feng; Gunnarsson, Fredrik; Amirijoo, Mehdi; Özkan, Emre; Gustafsson, Fredrik (2010-07-26) The particle filter provides a general solution to the nonlinear filtering problem with arbitrarily accuracy. However, the curse of dimensionality prevents its application in cases where the state dimensionality is high. Further, estimation of stationary parameters is a known challenge in a particle filter framework. We suggest a marginalization approach for the case of unknown noise distribution parameters that avoid both aforementioned problem. First, the standard approach of augmenting the state vector w...
Shape recognition with generalized beam angle statistics Tola, OO; Arica, N; Yarman Vural, Fatoş Tunay (2004-04-30) In this study, we develop a new shape descriptor and matching algorithm in order to find a given template shape in an edge detected image without performing boundary extraction. The shape descriptor based on Generalized Beam Angle Statistics (GBAS) defines the angles between the lines connecting each boundary point with the rest of the points, as random variable. Then, it assigns a feature vector to each point using the moments of beam angles. The proposed matching algorithm performs shape recognition by ma...
Direction finding with a uniform circular array via single snapshot processing Koc, AT; Tanik, Y (1997-01-01) In this work a new algorithm for multiple emitter direction finding by using a uniform circular array is proposed. The algorithm is based on single snapshot processing, and therefore, it has no restriction on the coherency of the sources. The problem formulation is based on the transformation of the snapshot. The transformed sequence is formed by taking the discrete Fourier transform of the snapshot and weighting it suitably. It contains the so-called distortion terms, which are taken into account by using ...

Citation Formats

I. K. Cihan and H. G. ŞENEL, “Gray Level Topological Angle Detection of High Curvature Points,” Bari, ITALY, 2010, p. 1618, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65335.