Gray level topological corner detection

Date

2007-06-07

Author

Cihan, Ibrahim Kivanc
Senel, Hakan Gueray

Metadata

Show full item record

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

Item Usage Stats

183
views

0
downloads

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.

Subject Keywords

Filters, Image edge detection, Pixel, Detection algorithms, Digital images, Object detection, Morphology, Brightness, Circuit topology, Shape

URI

https://hdl.handle.net/11511/65387

DOI

https://doi.org/10.1109/isie.2007.4374865

Conference Name

IEEE International Symposium on Industrial Electronics

Collections

Unclassified, Conference / Seminar

Suggestions

OpenMETU
Core

Gray Level Topological Angle Detection of High Curvature Points Cihan, Ibrahim Kivanc; ŞENEL, HAKAN GÜRAY (2010-07-07) 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.
HYPERSPECTRAL UNMIXING BASED VEGETATION DETECTION WITH SEGMENTATION Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Duzgun, Sebnem (2016-07-15) This paper presents a vegetation detection application with semi-supervised target detection using hyperspectral unmixing and segmentation algorithms. The method firstly compares the known target spectral signature from a generic source such as a spectral library with each pixel of hyperspectral data cube employing Spectral Angle Mapper (SAM) algorithm. The pixel(s) with the best match are assumed to be the most likely target vegetation locations. The regions around these potential target locations are furt...
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...
Efficient Bayesian track-before-detect Tekinalp, Serhat; Alatan, Abdullah Aydın (2006-10-11) This paper presents a novel Bayesian recursive track-before-detect (TBD) algorithm for detection and tracking of dim targets in optical image sequences. The algorithm eliminates the need for storing past observations by recursively incorporating new data acquired through sensor to the existing information. It calculates the likelihood ratio for optimal detection and estimates target state simultaneously. The technique does not require velocity-matched filtering and hence, it is capable of detecting any targ...
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...

Citation Formats

I. K. Cihan and H. G. Senel, “Gray level topological corner detection,” Vigo, SPAIN, 2007, p. 1727, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65387.