Fabric defect detection using the wavelet transform in an ARM processor

Fernández, José A; Orjuela, S. A.; Alvarez, Julio César; Philips, Wilfried

doi:10.1117/12.909432

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…The dominant architecture in the embedded electronics market is based in ARM processors, which are suitable for low power applications due to its relative simplicity [14]. Applications of ARM processors include electronic products like mobile phones, tablets, video games and computer peripherals such as hard drives and routers.…”

Section: Arm Embedded Systemmentioning

confidence: 99%

Architectural Evaluation of Algorithms RSA, ECC and MQQ in Arm Processors

Quirino¹,

Moreno²

2013

IJCNC

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Embedded devices are present in many of our daily activities. In some of these activities is necessary to protect the data from possible attacks. Due to resource constraints, it is necessary to study security techniques that consume the least possible resources of embedded platforms. This paper presents the performance evaluation of asymmetric cryptographic algorithms in embedded systems with Advanced RISC Machine (ARM) processor. The algorithms studied were Rivest-Shamir-Adleman (RSA), Elliptic Curve Cryptography (ECC) and Multivariate Quadratic Quasigroup (MQQ). We have used three criteria in our comparison: the processing time, memory and processor usage. We used the SimpleScalar tool for our simulations analysis. The results showed that MQQ is a good algorithm for embedded systems since it is better than ECC and RSA.

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Section: Arm Embedded Systemmentioning

confidence: 99%

Architectural Evaluation of Algorithms RSA, ECC and MQQ in Arm Processors

Quirino¹,

Moreno²

2013

IJCNC

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“…These inspection methods use image processing and analysis to determine nonconformity of products based on predetermined criteria, and have been successfully used to detect surface defects on LCD screens [5], ceramic and tiles [6], steel [7]- [9], and textiles [10], [11]. Visual inspection techniques were also used to evaluate nonuniformity on surfaces of bottle caps [12] and detect defects on solar modules [13].…”

Section: Introductionmentioning

confidence: 99%

A Contrast Adjustment Thresholding Method for Surface Defect Detection Based on Mesoscopy

Win

Bushroa

Hassan

et al. 2015

IEEE Trans. Ind. Inf.

114

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Titanium-coated surfaces are prone to tiny defects such as very small cracks, which are not easily observable by the naked eye or optical microscopy. In this study, two new thresholding methods, namely contrast-adjusted Otsu's method and contrast-adjusted median-based Otsu's method, are proposed for automated defect detection system for titanium-coated aluminum surfaces. The two proposed methods were compared with four existing thresholding techniques in terms of accuracy and speed of defect detections for images of 700, 900, and 1000 dpi obtained using high-resolution scanning. Experimental results have shown that the proposed contrast-adjusting methods have performance similar to minimum error thresholding (MET) and are generally better than Otsu's method.

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Real-time portable system for fabric defect detection using an ARM processor

et al. 2012

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Modern textile industry seeks to produce textiles as little defective as possible since the presence of defects can decrease the final price of products from 45% to 65%. Automated visual inspection (AVI) systems, based on image analysis, have become an important alternative for replacing traditional inspections methods that involve human tasks. An AVI system gives the advantage of repeatability when implemented within defined constrains, offering more objective and reliable results for particular tasks than human inspection.Costs of automated inspection systems development can be reduced using modular solutions with embedded systems, in which an important advantage is the low energy consumption. Among the possibilities for developing embedded systems, the ARM processor has been explored for acquisition, monitoring and simple signal processing tasks. In a recent approach we have explored the use of the ARM processor for defects detection by implementing the wavelet transform. However, the computation speed of the preprocessing was not yet sufficient for real time applications.In this approach we significantly improve the preprocessing speed of the algorithm, by optimizing matrix operations, such that it is adequate for a real time application. The system was tested for defect detection using different defect types. The paper is focused in giving a detailed description of the basis of the algorithm implementation, such that other algorithms may use of the ARM operations for fast implementations.

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Fabric defect detection using the wavelet transform in an ARM processor

Cited by 3 publications

References 17 publications

Architectural Evaluation of Algorithms RSA, ECC and MQQ in Arm Processors

Architectural Evaluation of Algorithms RSA, ECC and MQQ in Arm Processors

A Contrast Adjustment Thresholding Method for Surface Defect Detection Based on Mesoscopy

Real-time portable system for fabric defect detection using an ARM processor

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