Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A Feature Extraction Method for Marble Tile Classification
Date
2000-03-03
Author
DEVİREN, Murat
M KORAY, Balcı
Leloğlu, Uğur Murat
SEVERCAN, Mete
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
226
views
0
downloads
Cite This
This study focuses on a feature extraction algorithm for classification of marble tiles. The color content and vein distribution are considered to be the main criteria for classification. A color segmentation algorithm is used for detection of veins. The shape analysis of the veins are done by utilizing the distance image.
Subject Keywords
Color images
,
Segmentation
URI
https://hdl.handle.net/11511/53631
Collections
Graduate School of Natural and Applied Sciences, Conference / Seminar
Suggestions
OpenMETU
Core
A Shadow based trainable method for building detection in satellite images
Dikmen, Mehmet; Halıcı, Uğur; Department of Geodetic and Geographical Information Technologies (2014)
The purpose of this thesis is to develop a supervised building detection and extraction algorithm with a shadow based learning method for high-resolution satellite images. First, shadow segments are identified on an over-segmented image, and then neighboring shadow segments are merged by assuming that they are cast by a single building. Next, these shadow regions are used to detect the candidate regions where buildings most likely occur. Together with this information, distance to shadows towards illuminati...
A Graph-Based Approach for Video Scene Detection
Sakarya, Ufuk; Telatar, Zjya (2008-04-22)
In this paper, a graph-based method for video scene detection is proposed. The method is based on a weighted undirected graph. Each shot is a vertex on the graph. Edge weights among the vertices are evaluated by using spatial and temporal similarities of shots. By using the complete information of the graph, a set of the vertices mostly similar to each other and dissimilar to the others is detected. Temporal continuity constraint is achieved on this set. This set is the first detected video scene. The verti...
SUPER PIXEL EXTRACTION VIA CONVEXITY INDUCED BOUNDARY ADAPTATION
Tasli, H. Emrah; Cigla, Cevahir; Gevers, Theo; Alatan, Abdullah Aydın (2013-07-19)
This study presents an efficient super-pixel extraction algorithm with major contributions to the state-of-the-art in terms of accuracy and computational complexity. Segmentation accuracy is improved through convexity constrained geodesic distance utilization; while computational efficiency is achieved by replacing complete region processing with boundary adaptation idea. Starting from the uniformly distributed rectangular equal-sized super-pixels, region boundaries are adapted to intensity edges iterativel...
Prediction of multiphase flow properties from nuclear magnetic resonance imaging
Karaman, Türker; Akın, Serhat; Department of Petroleum and Natural Gas Engineering (2009)
In this study a hybrid Pore Network (PN) model that simulates two-phase (water-oil) drainage and imbibition mechanisms is developed. The developed model produces Nuclear Magnetic Resonance (NMR) T2 relaxation times using correlations available in the literature. The developed PN was calibrated using experimental relative permeability data obtained for Berea Sandstone, Kuzey Marmara Limestone, Yeniköy Dolostone and Dolomitic Limestone core plugs. Pore network body and throat parameters were obtained from ser...
An automatic geo-spatial object recognition algorithm for high resolution satellite images
Ergul, Mustafa; Alatan, Abdullah Aydın (2013-09-26)
This paper proposes a novel automatic geo-spatial object recognition algorithm for high resolution satellite imaging. The proposed algorithm consists of two main steps; a hypothesis generation step with a local feature-based algorithm and a verification step with a shape-based approach. In the hypothesis generation step, a set of hypothesis for possible object locations is generated, aiming lower missed detections and higher false-positives by using a Bag of Visual Words type approach. In the verification s...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. DEVİREN, B. M KORAY, U. M. Leloğlu, and M. SEVERCAN, “A Feature Extraction Method for Marble Tile Classification,” 2000, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53631.