Wyniki wyszukiwania - BazTech

1

Automatic parameters selection of Gabor filters with the imperialism competitive algorithm with application to retinal vessel segmentation

Farokhian F., Yang C., Demirel H., Wu S., Beheshti I.

Biocybernetics and Biomedical Engineering

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2017

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Vol. 37, no. 1

246--254

EN

Retinal images play an important role in the early diagnosis of diseases such as diabetes. In the present study, an automatic image processing technique is proposed to segment retinal blood vessels in fundus images. The technique includes the design of a bank of 180 Gabor filters with varying scale and elongation parameters. Furthermore, an optimization method, namely, the imperialism competitive algorithm (ICA), is adopted for automatic parameter selection of the Gabor filter. In addition, a systematic method is proposed to determine the threshold value for reliable performance. Finally, the performance of the proposed approach is analyzed and compared with that of other approaches on the basis of the publicly available DRIVE database. The proposed method achieves an area under the receiver operating characteristic curve of 0.953 and an average accuracy of up to 0.9392. Thus, the results show that the proposed method is well comparable with alternative methods in the literature.

2

Real-Time Denim Fabric Inspection Using Image Analysis

Çelik H. I., Topalbekitoglu M., Dülger L. C.

Fibres & Textiles in Eastern Europe

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2015

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Vol. 23, no. 3 (111)

85--90

EN

In spite of using modern weaving technology, many types of fabric defects occur during production. Most defects arising in the production process of a fabric are still detected by human inspection. A machine vision system that can be adapted to different types of fabric inspection machines is proposed in this study. Image frames of denim fabric were acquired using a CCD line-scan camera. An algorithm was developed by using the Gabor filter and double thresholding methods. The performance of the algorithm was tested real-time by analysing a denim fabric sample which contained six types of defects: hole, warp lacking, weft lacking, soiled yarn, water soil and yarn flow (knot). The defective regions of the denim fabric sample were detected and labelled successfully.

PL

Mimo stosowania współczesnych technologii tkackich, wiele typów defektów tkaniny powstaje podczas ich produkcji. Większość defektów podczas procesu produkcji tkaniny w dalszym ciągu jest wykrywana poprzez kontrolę pracowników. W pracy zaproponowano automatyczny system inspekcji wizualnej, który można adoptować do różnych typów maszyn, realizujących inspekcje tkaniny. Wykonano ramki ilustrujące tkaninę typu Denim przy zastosowaniu liniowej kamery skanującej typu CCD. Opracowano algorytm stosując filtr Gabor A i metodę podwójnego progu dyskryminującego. Skuteczność algorytmu testowano analizując próbki tkaniny Denim zawierające 6 typów defektów - dziura, brak osnowy, brak wątku, zabrudzona przędza, zmoczona przędza i pęczki. Sukcesywnie określano zaznaczone uszkodzenia.

3

Texture Analysis for 3D Classification of Brain Tumor Tissues

Arunadevi B., Deepa S.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 4

338-342

EN

This paper investigates on extending and comparing the Gray level co-occurrence matrices (GLCM) and 3D Gabor filters in volumetric texture analysis of brain tumor tissue classification. The extracted features are sub-selected by genetic algorithm for dimensionality reduction and fed into Extreme Learning Machine Classifier. The organizational prototype of image voxels distinctive to the underlying substrates in a tissue is been evaluated and validated on public and clinical dataset revealing 3D GLCM more appropriate towards brain tumor tissue classification.

PL

W artykule zbadano i porównano algorytmy klasyfikacji tkanki guza mózgu – GLCM i filtry Gabora 3D. Właściwości ekstrakcji były selekcjonowane przy użyciu algorytmu genetycznego i klasyfikatora ELM.

4

An improved algorithm for feature extraction from a fingerprint fuzzy image

Surmacz K., Saeed K., Rapta P.

Optica Applicata

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2013

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Vol. 43, nr 3

515--527

EN

Proper fingerprint feature extraction is crucial in fingerprint-matching algorithms. For good results, different pieces of information about a fingerprint image, such as ridge orientation and frequency, must be considered. It is often necessary to improve the quality of a fingerprint image in order for the feature extraction process to work correctly. In this paper we present a complete (fully implemented) improved algorithm for fingerprint feature extraction, based on numerous papers on this topic. The paper describes a fingerprint recognition system consisting of image preprocessing, filtration, feature extraction and matching for recognition. The image preprocessing includes normalization based on mean value and variation. The orientation field is extracted and Gabor filter is used to prepare the fingerprint image for further processing. For singular point detection, the Poincaré index with a partitioning method is used. The ridgeline thinning is presented and so is the minutia extraction by CN algorithm. The paper contains the comparison of obtained results to the other algorithms.

5

Classification of color textures by gabor filtering

Palm C., Lehman T. M.

Machine Graphics and Vision

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2002

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Vol. 11, No. 2/3

195-219

EN

A novel approach to Gabor filtering of color textures in introduced. It is based on the complex chromatic Fourier transform.Complex colors are derived from the HSL color space representing intensity-independent color textures.Additionally, a novel Gabor texture feature for the grayscale as well as the color domain is proposed. It relies on local phase changes characterizing the homogeneity of a texture in the spatial frequency domain. Several classification experiments on two image databases are performed to study the texture features according to different color spaces and Gabor filter bank variants. The color features show significantly better results than the grayscale features. Although they are completely intensity-independent, the features on the basis of the complex color space show satisfying results. The RGB based features, where color and intensity work inherently together, perform best. Especially the local phase change measure supplements the known amplitude measure appropriately.