Shoeprint retrieval: Core point alignment for pattern comparison

Gwo, Chih-Ying; Wei, Chia-Hung

doi:10.1016/j.scijus.2016.06.004

Cited by 11 publications

(5 citation statements)

References 27 publications

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“…The ultimate question we have addressed was that whether generalisations drawn from generic system testing would hold for individual speakers under different conditions. Numerous studies (Gwo & Wei, 2016;Morrison, 2016;Morrison & Enzinger, 2016) have discussed the validity and reliability issues in forensic evidence evaluation; however, the variability in LR output observed in the current study has not been addressed in the field of FVC. We propose that overall performance should be tested multiple times using different sets/configurations of training and reference data and the individual speakers' behaviour should be investigated and reported as part of the system testing.…”

Section: Discussionmentioning

confidence: 83%

The effect of sampling variability on systems and individual speakers in likelihood ratio-based forensic voice comparison

Wang

Hughes

Foulkes

2022

Speech Communication

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Section: Discussionmentioning

confidence: 83%

The effect of sampling variability on systems and individual speakers in likelihood ratio-based forensic voice comparison

Wang

Hughes

Foulkes

2022

Speech Communication

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“…The aim of this study is to investigate the effect of sampling variability on overall performance and individual speakers' behaviour in data-driven LR-based FVC. Numerous studies (e.g., Gwo & Wei, 2016;Morrison, 2016; have discussed the validity and reliability issues in forensic evidence evaluation; however, the variability in LR output observed in the current study has not previously been addressed in the field of FVC.…”

Section: Discussionmentioning

confidence: 76%

The effect of sampling variability on overall performance and individual speakers’ behaviour in likelihood ratio-based forensic voice comparison

Wang

2022

The International Journal of Speech, Language and the Law

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In the past years, there is increasing awareness and acceptance among forensic speech scientists of using Bayesian reasoning and likelihood ratio (LR) framework for forensic voice comparison (FVC) and expressing expert conclusions. Numerous studies have explored overall performance using numerical LRs. Given that the data used for validation is a sample coming from an unknown distribution, little attention has been paid to the effect of sampling variability or individuals' behaviour. This thesis investigates these issues using linguistic-phonetic variables. First, it investigates how different configurations of training, test and reference speakers affect overall performance. The results show that variability in overall performance is mostly caused by varying the test speakers, while less variability is caused by sampling variability in the reference and training speakers. Second, this thesis explores the effect of sampling variability on overall performance and individuals' behaviour in relation to the use of linguistic-phonetic features. Results show that sampling variability affects overall performance to different extents using different features, while combining more features does not always improve overall performance. Sampling variability has limited effects on individuals in same-speaker comparisons, and most speakers are less affected by sampling variability in different-speaker comparisons when four or more features are used. Third, this thesis explores the effect of sampling variability on overall performance in relation to score distributions. Results reveal that system validity and reliability are more affected by differentspeaker score skewness, and less affected by same-speaker score skewness. Using different calibration methods reduces the effect of sampling variability to different extents. The resultsin this thesis have implications for both FVC using numerical LRs and FVC in general, as experts need to make pragmatic decisions whether numerical LR is used or not, and every decision made has implication to final evaluation results. Further, the results on score skewness and different calibration methods have potential contribution for improving FVC performance using automatic systems.

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“…In this study, Zernike polynomials were expressed in polar coordinates defined on a unit disc, which are a complete set of orthogonal basis functions (Papakostas et al, 2007; Wee and Paramesran, 2007). The lower-order ZMs describe global contour and gross shape features, and the higher-order ZMs describe regional and fine topological details of a shape (Gwo and Wei, 2016). Of note, the magnitudes of ZMs are not only rotational invariant but also robust to small perturbations on the contour of a shape image (Teh and Chin, 1988).…”

Section: Methods and Resultsmentioning

confidence: 99%

Brain White Matter Hyperintensity Lesion Characterization in T2 Fluid-Attenuated Inversion Recovery Magnetic Resonance Images: Shape, Texture, and Potential Growth

2019

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Prior methods in characterizing age-related white matter hyperintensity (WMH) lesions on T 2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance images (MRI) have mainly been limited to understanding the sizes of, and occasionally the locations of WMH lesions. Systematic morphological characterization has been missing. In this work, we proposed innovative methods to fill this knowledge gap. We developed an innovative and proof-of-concept method to characterize and quantify the shape (based on Zernike transformation) and texture (based on fuzzy logic) of WMH lesions. We have also developed a multi-dimension feature vector approach to cluster WMH lesions into distinctive groups based on their shape and then texture features. We then developed an approach to calculate the potential growth index (PGI) of WMH lesions based on the image intensity distributions at the edge of the WMH lesions using a region-growing algorithm. High-quality T 2 FLAIR images containing clearly identifiable WMH lesions with various sizes from six cognitively normal older adults were used in our method development Analyses of Variance (ANOVAs) showed significant differences in PGI among WMH group clusters in terms of either the shape ( P = 1.06 × 10 −2 ) or the texture ( P < 1 × 10 −20 ) features. In conclusion, we propose a systematic framework on which the shape and texture features of WMH lesions can be quantified and may be used to predict lesion growth in older adults.

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Shoeprint retrieval: Core point alignment for pattern comparison

Cited by 11 publications

References 27 publications

The effect of sampling variability on systems and individual speakers in likelihood ratio-based forensic voice comparison

The effect of sampling variability on systems and individual speakers in likelihood ratio-based forensic voice comparison

The effect of sampling variability on overall performance and individual speakers’ behaviour in likelihood ratio-based forensic voice comparison

Brain White Matter Hyperintensity Lesion Characterization in T2 Fluid-Attenuated Inversion Recovery Magnetic Resonance Images: Shape, Texture, and Potential Growth

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