MAJTNER, Tomáš and David SVOBODA. 2D/3D Gabor Features and 2D/3D MPEG-7 EHD Features. 2015.
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Basic information
Original name 2D/3D Gabor Features and 2D/3D MPEG-7 EHD Features
Authors MAJTNER, Tomáš (703 Slovakia, belonging to the institution) and David SVOBODA (203 Czech Republic, guarantor, belonging to the institution).
Edition 2015.
Other information
Original language English
Type of outcome Software
Field of Study 20206 Computer hardware and architecture
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW http://cbia.fi.muni.cz/projects/2d/3d-gabor--2d/3d-mpeg-7-ehd-features.html
RIV identification code RIV/00216224:14330/15:00081208
Organization unit Faculty of Informatics
Keywords in English image descriptor; Pattern recognition; Gabor features; MPEG-7 Edge Histogram Descriptor;
Technical parameters Software pre výpis textúrových vlastností snímku na základe aplikovania metód Gabor features a MPEG-7 EHD, ktoré je možné použiť pre rozpoznanie a následnú klasifikáciu vstupného obrázku. Primárnou inováciou je pridaná podpora pre aplikovanie na 3D vstupné data, ktorá doposiaľ nebola definovaná. Program bol vyvinutý pre spracovanie biomedicínskych obrázkov nasnímaných fluorescenčným mikroskopom ale obecne je možné ho použiť pre ľubovolný vstup. Implementácia je realizovaná v jazyku C++. Zodpovedné osoby: Tomáš Majtner <majtner@ics.muni.cz> a David Svoboda<svoboda@fi.muni.cz> Adresa: Fakulta informatiky Masarykovy univerzity, Botanická 68a, 602 00 Brno.
Tags cbia-web
Tags International impact
Changed by Changed by: RNDr. Ing. Bc. Tomáš Majtner, Ph.D., učo 172786. Changed: 19/11/2015 11:08.
Abstract
The recognition of patterns with focus on texture and shape analysis is still very hot topic, especially in biomedical image processing. In this article, we introduce 3D extensions of well-known approaches for this particular area. We focus on the collection of MPEG-7 image descriptors, specifically on the Edge Histogram Descriptor (EHD) and Gabor features, which are the core of the Homogeneous Texture Descriptor (HTD). The proposed extensions are evaluated on the dataset consisting of three classes of 3D volumetric biomedical images. Two different classifiers, namely k-NN and Multi-Class SVM, are used to evaluate the proposed algorithms. According to the presented tests, the proposed 3D extensions clearly outperform their 2D equivalents in the classification tasks.
Links
GA14-22461S, research and development projectName: Vývoj a studium metod pro kvantifikaci živých buněk (Acronym: Live Cell Quantification)
Investor: Czech Science Foundation
MUNI/A/1159/2014, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace IV.
Investor: Masaryk University, Category A
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