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Fabric Defect Detection Adopting Combined GLCM, Gabor Wavelet Features and Random Decision Forest

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Abstract

In image analysis and pattern recognition activity, one of the most salient characteristics is texture. The global region of images in spatial domain has an enhanced processing effect with the help of co-occurrence matrix and in the frequency domain for the admirable performance such as multi-scale, multi-direction local information is obtained from Gabor wavelet. The consolidation of gray-level co-occurrence matrix and Gabor wavelet is utilized to fabric image feature texture eradication. In classification phase, random decision forest (RDFs) Classifier is applied to classify the input fabric image into defective or non-defective. RDFs are a novel and outfit machine learning strategy which fuses the element choice. Nevertheless, RDFs exhibit a lot of advantages when compared with other modeling approaches within the category. The main advantages are, RDFs can handle both the continuous and discrete variables, RDFs does not overfit as a classifier, and run quick and productively when taking care of expansive datasets.

Graphical Abstract

In this paper the consolidation of gray-level co-occurrence matrix (GLCM) and Gabor wavelet is utilized to fabric image feature texture eradication. In classification phase, random decision forest (RDFs) classifier is applied to classify the input fabric image into defective or non-defective.

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Abbreviations

GLCM:

Gray-level co-occurrence matrix

RDFs:

Random decision forest

2D:

Two-dimensional

LVQ:

Learning vector quantization

GGD:

Generalized Gaussian density

ML:

Maximum likelihood

ANN:

Artificial neural network

MRF:

Markov random field

LCP:

Local comprehensive patterns

ILS:

Isotropic lattice segmentation

LSG:

Lattice segmentation assisted by Gabor filters

MCA:

Morphological component analysis

VOV:

Variance of variance

LMGCP:

Local multi-channels Gabor comprehensive patterns

LGMM:

Local Gabor magnitude map

DDP:

Direction derivatives patterns

DMP:

Direction magnitude patterns

AMF:

Adaptive median filter

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Authors and Affiliations

  1. Computer Engineering Department, Thadomal Shahani College of Engineering, Mumbai, India

    Nilesh Tejram Deotale & Tanuja K. Sarode

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Correspondence to Nilesh Tejram Deotale.

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Deotale, N.T., Sarode, T.K. Fabric Defect Detection Adopting Combined GLCM, Gabor Wavelet Features and Random Decision Forest. 3D Res 10, 5 (2019). https://doi.org/10.1007/s13319-019-0215-1

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