Wavelets and Gaussian mixture model approach for gender classification using fingerprints

Rajesh, D. Gnana; Punithavalli, M.

doi:10.1109/icctet.2014.6966352

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Moreover, it has better crack resistance and increased fire and thermal resistance [74]. The slump value of ferrock as a replacement for concrete is in accordance with the mix design specifications [75]. Nevertheless, ferrock's iron powder contains microparticles that pose health risks during the manufacturing process [71], and although it is cheaper than concrete, its price could see a significant increase if the demand for ferrock increases [76].…”

Section: Ferrockmentioning

confidence: 99%

A Quantitative Group Decision-Making Methodology for Structural Eco-Materials Selection Based on Qualitative Sustainability Attributes

Al Shdifat,

Jalón,

Puertas

et al. 2023

Applied Sciences

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In response to escalating global environmental challenges, developed countries have embarked on an ecological transition across a range of sectors. Among these, the construction industry plays a key role due to its extensive use of raw materials and energy resources. In particular, research into sustainable construction materials, here named eco-materials, has seen a boost in recent years because of their potential to replace less environmentally friendly materials such as concrete and steel. This paper proposes a large-scale group decision-making methodology to select among a set of candidate structural eco-materials based on sustainability considerations. The proposed approach is based on a novel quantitative SWOT analysis using survey data from a diverse group of experts, considering not only the technical aspects of the materials but also their impact in the context of the United Nations’ Sustainable Development Goals. As a result, a range of eco-materials are probabilistically assessed and ranked, taking into account the variability and uncertainty in the survey data. The results of this research demonstrate the suitability of the proposed methodology for eco-material selection based on sustainability criteria, but also provide a new generic methodology for group decision assessment considering the uncertainty in the survey data, which can be extended to multiple applications.

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Section: Ferrockmentioning

confidence: 99%

A Quantitative Group Decision-Making Methodology for Structural Eco-Materials Selection Based on Qualitative Sustainability Attributes

Al Shdifat,

Jalón,

Puertas

et al. 2023

Applied Sciences

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“…Gender classification using fingerprints based on Gaussian Mixture Model (GMM) and wavelets is discussed in [5]. The input fingerprint images are decomposed by DWT.…”

Section: Introductionmentioning

confidence: 99%

Gender Identification System for Crime Scence Analysis Using Fingerprints

Jaison¹

2017

International Journal of Advances in Signal and Image Sciences

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Gender identification or classification is a challenging task in computer vision as the biometrics of male and female such as fingerprints, face, vein have many variations. Among the various biometrics, fingerprints are commonly available in a crime scene. In this, study, gender identification system for crime scene analysis using fingerprints is presented. Initially, the fingerprints are de-noised by median filter and Otsu thresholding is employed to binarize the fingerprints in the preprocessing stage. Then, the features are extracted by Box-Cox transformation method. Finally, the classification is made by logistic regression classifier. A better classification accuracy of 96% is achieved by the gender identification system using Box-Cox transformation and logistic regression classifier.

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“…Many research publication works discover and appraise the weakness of gender classification accuracy problem [10], while some researcher propose of a new classification methods for gender classification problem [11][12] [13] and several publications enhance the accuracy by comparing the classification rate using different classifier [3] [14].…”

Section: Introductionmentioning

confidence: 99%

Development of a Fingerprint Gender Classification Algorithm Using Fingerprint Global Features

Abdullah¹,

Rahman²,

Abas³

et al. 2016

ijacsa

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Abstract-In forensic world, the process of identifying and calculating the fingerprint features is complex and take time when it is done manually using fingerprint laboratories magnifying glass. This study is meant to enhance the forensic manual method by proposing a new algorithm for fingerprint global feature extraction for gender classification. The result shows that the new algorithm gives higher acceptable readings which is above 70% of classification rate when it is compared to the manual method. This algorithm is highly recommended in extracting a fingerprint global feature for gender classification process.

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Wavelets and Gaussian mixture model approach for gender classification using fingerprints

Cited by 4 publications

References 7 publications

A Quantitative Group Decision-Making Methodology for Structural Eco-Materials Selection Based on Qualitative Sustainability Attributes

A Quantitative Group Decision-Making Methodology for Structural Eco-Materials Selection Based on Qualitative Sustainability Attributes

Gender Identification System for Crime Scence Analysis Using Fingerprints

Development of a Fingerprint Gender Classification Algorithm Using Fingerprint Global Features

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