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Journal articles on the topic 'Shape principal component analysis'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

CHANG, CHIN-CHEN, YAW-WEN CHEN, and DANIEL JAMES BUEHRER. "A TWO-DIMENSIONAL SHAPE RECOGNITION SCHEME BASED ON PRINCIPAL COMPONENT ANALYSIS." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 04 (1994): 859–75. http://dx.doi.org/10.1142/s0218001494000449.

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In this paper, we propose a simple, but efficient method to recognize two-dimensional shapes without regard to their translation, rotation, and scaling factors. In our scheme, we use all of the boundary points to calculate the first principal component, which is the first shape feature. Next, by dividing the boundary points into groups by projecting them onto the first principal component, each shape is partitioned into several blocks. These blocks are processed separately to produce the remaining shape features. In shape matching, we compare two shapes by calculating the difference between th

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Cadima, Jorge F. C. L., and Ian T. Jolliffe. "Size- and Shape-Related Principal Component Analysis." Biometrics 52, no. 2 (1996): 710. http://dx.doi.org/10.2307/2532909.

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Takalo, Jouni, and Kalevi Mursula. "Principal component analysis of sunspot cycle shape." Astronomy & Astrophysics 620 (December 2018): A100. http://dx.doi.org/10.1051/0004-6361/201833924.

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Aims. We study the shape of sunspot cycles using the Wolf sunspot numbers and group sunspot numbers of solar cycles 1–23. We determine the most typical “model” cycles and the most asymmetric cycles, and test the validity of the two Waldmeier rules: the anti-correlation between cycle height and the length of its ascending phase (rule 1), and between cycle height and the length of the preceding cycle (rule 2). Methods. We applied the principal component analysis to sunspot cycles and studied the first two components, which describe the average cycle shape and cycle asymmetry, respectively. We al

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Orsborn, Seth, Peter Boatwright, and Jonathan Cagan. "Identifying product shape relationships using principal component analysis." Research in Engineering Design 18, no. 4 (2007): 163–80. http://dx.doi.org/10.1007/s00163-007-0036-8.

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5

Iyengar, Prasana A. "Natural shape detection based on principal component analysis." Journal of Electronic Imaging 2, no. 3 (1993): 253. http://dx.doi.org/10.1117/12.148220.

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6

Huckemann, Stephan, and Thomas Hotz. "Principal component geodesics for planar shape spaces." Journal of Multivariate Analysis 100, no. 4 (2009): 699–714. http://dx.doi.org/10.1016/j.jmva.2008.08.008.

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Li, Peng, Brian Corner, and Steven Paquette. "Shape analysis of female torsos based on discrete cosine transform." International Journal of Clothing Science and Technology 27, no. 5 (2015): 677–91. http://dx.doi.org/10.1108/ijcst-03-2014-0035.

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Purpose – The purpose of this paper is to present results of shape analysis of female torso shape using the discrete cosine transform (DCT) from a three-dimensional (3D) whole body scan database. Design/methodology/approach – Torso shape is a central part of body shape and difficult to describe by linear measurements. In order to analyze body shape variation within a population the authors employed a DCT-based shape description method to compresses a dense 3D body scan surface into a small vector that preserves shape and removes size. The DCT-based shape descriptors of torso surfaces are furth

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Wilson, Susan, and Danuta Loesch. "Principal component analysis of shape variables in adult individuals." Annals of Human Biology 16, no. 4 (1989): 361–68. http://dx.doi.org/10.1080/03014468900000482.

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Gwashavanhu, Benjamin Katerere, Abrie J. Oberholster, and Stephan P. Heyns. "A comparative study of principal component analysis and kernel principal component analysis for photogrammetric shape-based turbine blade damage analysis." Engineering Structures 318 (November 2024): 118712. http://dx.doi.org/10.1016/j.engstruct.2024.118712.

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Vasic, Mirjana, Jelica Gvozdanovic-Varga, and Janko Cervenski. "Divergence in the dry bean collection by Principal Component Analysis (PCA)." Genetika 40, no. 1 (2008): 23–30. http://dx.doi.org/10.2298/gensr0801023v.

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We studied the divergence of our beans collection. The study included two qualitative traits, grain color and shape, and 13 quantitative traits, namely three components of plant height, five direct yield components and five chemical properties of grain. The principal component analysis (PCA) showed which of the traits were decisive in genotype differentiation. The principal components were formed based on the correlation matrix and shown through unrotated and rotated values of trait correlation with the main axes. The percentage contribution of particular principal components to total variabil

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Huckemann, Stephan, and Herbert Ziezold. "Principal component analysis for Riemannian manifolds, with an application to triangular shape spaces." Advances in Applied Probability 38, no. 2 (2006): 299–319. http://dx.doi.org/10.1239/aap/1151337073.

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Classical principal component analysis on manifolds, for example on Kendall's shape spaces, is carried out in the tangent space of a Euclidean mean equipped with a Euclidean metric. We propose a method of principal component analysis for Riemannian manifolds based on geodesics of the intrinsic metric, and provide a numerical implementation in the case of spheres. This method allows us, for example, to compare principal component geodesics of different data samples. In order to determine principal component geodesics, we show that in general, owing to curvature, the principal component geodesic

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Huckemann, Stephan, and Herbert Ziezold. "Principal component analysis for Riemannian manifolds, with an application to triangular shape spaces." Advances in Applied Probability 38, no. 02 (2006): 299–319. http://dx.doi.org/10.1017/s0001867800000987.

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Classical principal component analysis on manifolds, for example on Kendall's shape spaces, is carried out in the tangent space of a Euclidean mean equipped with a Euclidean metric. We propose a method of principal component analysis for Riemannian manifolds based on geodesics of the intrinsic metric, and provide a numerical implementation in the case of spheres. This method allows us, for example, to compare principal component geodesics of different data samples. In order to determine principal component geodesics, we show that in general, owing to curvature, the principal component geodesic

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Gentallan, Renerio P., Nestor C. Altoveros, Teresita H. Borromeo, et al. "An objective method of shape descriptor state establishment using elliptic Fourier analysis (EFA)." Plant Genetic Resources: Characterization and Utilization 17, no. 6 (2019): 480–87. http://dx.doi.org/10.1017/s1479262119000285.

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AbstractThis research attempts to systematically establish shape descriptor states through elliptic Fourier analysis (EFA) using pili (Canarium ovatum Engl.) kernel as a model. Kernel images of 53 pili accessions from the National Plant Genetic Resources Laboratory (NPGRL), University of the Philippines Los Baños were acquired using VideometerLab 3. Shape features, such as roundness, compactness and elongation, were extracted from the images. Shapes outlines were characterized using elliptic Fourier coefficients calculated from SHAPE version 1.3 software. Principal component analysis and clust

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Huang, R., E. Armengaud, C. Augier, et al. "Pulse shape discrimination in CUPID-Mo using principal component analysis." Journal of Instrumentation 16, no. 03 (2021): P03032. http://dx.doi.org/10.1088/1748-0221/16/03/p03032.

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Tuță, Leontin, Ioan Nicolaescu, Radu Mariescu-Istodor, and Angela Digulescu-Popescu. "A Principal Component Analysis (PCA) based Method for Shape Extraction." Journal of Military Technology 2, no. 2 (2019): 17–28. http://dx.doi.org/10.32754/jmt.2019.2.03.

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Keustermans, William, Toon Huysmans, Femke Danckaers, et al. "High quality statistical shape modelling of the human nasal cavity and applications." Royal Society Open Science 5, no. 12 (2018): 181558. http://dx.doi.org/10.1098/rsos.181558.

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The human nose is a complex organ that shows large morphological variations and has many important functions. However, the relation between shape and function is not yet fully understood. In this work, we present a high quality statistical shape model of the human nose based on clinical CT data of 46 patients. A technique based on cylindrical parametrization was used to create a correspondence between the nasal shapes of the population. Applying principal component analysis on these corresponded nasal cavities resulted in an average nasal geometry and geometrical variations, known as principal

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Guerrero-Morejón, Katherine, José María Hinojo-Montero, Fernando Muñoz-Chavero, Juan Luis Flores-Garrido, Juan Antonio Gómez-Galán, and Ramón González-Carvajal. "Principal Component Analysis Applied to Digital Pulse Shape Analysis for Isotope Discrimination." Sensors 23, no. 23 (2023): 9418. http://dx.doi.org/10.3390/s23239418.

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Digital pulse shape analysis (DPSA) techniques are becoming increasingly important for the study of nuclear reactions since the development of fast digitizers. These techniques allow us to obtain the (A, Z) values of the reaction products impinging on the new generation solid-state detectors. In this paper, we present a computationally efficient method to discriminate isotopes with similar energy levels, with the aim of enabling the edge-computing paradigm in future field-programmable gate-array-based acquisition systems. The discrimination of isotope pairs with analogous energy levels has bee

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Beauducel, André, and Norbert Hilger. "On Optimal Allocation of Treatment/Condition Variance in Principal Component Analysis." International Journal of Statistics and Probability 7, no. 4 (2018): 50. http://dx.doi.org/10.5539/ijsp.v7n4p50.

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The allocation of a (treatment) condition-effect on the wrong principal component (misallocation of variance) in principal component analysis (PCA) has been addressed in research on event-related potentials of the electroencephalogram. However, the correct allocation of condition-effects on PCA components might be relevant in several domains of research. The present paper investigates whether different loading patterns at each condition-level are a basis for an optimal allocation of between-condition variance on principal components. It turns out that a similar loading shape at each condition-

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Grant, Robyn A., Luca Taraborrelli, and Tom Allen. "Morphometrics for sports mechanics: Showcasing tennis racket shape diversity." PLOS ONE 17, no. 1 (2022): e0263120. http://dx.doi.org/10.1371/journal.pone.0263120.

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Tennis racket design has changed from its conception in 1874. While we know that modern tennis rackets are lighter and have larger heads than their wooden predecessors, it is unknown how their gross shape has changed specifically. It is also unknown how racket shape is related to factors that influence performance, like the Transverse and Polar moments of inertia. The aim of this study was to quantify how tennis racket shape has changed over time, with a view to furthering our understanding of how such developments have influenced the game. Two-dimensional morphometric analysis was applied to

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Grant, Robyn A., Vincent Bonhomme, and Tom Allen. "Generating novel tennis racket shape concepts using a theoretical morphospace." PLOS ONE 19, no. 9 (2024): e0310155. http://dx.doi.org/10.1371/journal.pone.0310155.

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Statistical shape analysis, or morphometrics, is a technique commonly used in evolutionary biology to summarise a population of samples. Theoretical morphometrics extends the current population of samples into a theoretical space. Using the lawn tennis racket as an example, this paper showcases the potential of morphometrics as a tool for inspiring design concepts for novel sporting goods. It showcases how morphometrics can be applied to summarise the shape of a sample of rackets and applies theoretical morphometrics to systematically present new candidate designs that fall outside of the inpu

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Fu, Lin, Kaczmarek Łukasz, Ci Jiang, and Yaodong Gu. "A Region-Based Statistical Shape Modeling on the First Trapezoid-Metacarpal." Applied Bionics and Biomechanics 2023 (February 1, 2023): 1–8. http://dx.doi.org/10.1155/2023/3257460.

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A statistical shape model (SSM) based analysis was conducted in our study. We indicated the morphological differences of the first trapezoid-metacarpal (TMC) bone between the region-based statistical shape model (rSSM) and the nonregion-based statistical shape model (nrSSM). We aimed to characterize more specific and accurate variation results to detect and prevent osteoarthritis in an early way. CT image data of TMC from 31 healthy volunteers were simulated with 3D models. A training set of models was analyzed with principal component analysis, with both then- rSSM and rSSM. The region was id

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22

Laksmana, Indra, Hendra Hendra, Sri Aulia Novita, et al. "Identification of Tropical Plants Leaves Image Base on Principal Component Analysis." Journal of Applied Agricultural Science and Technology 4, no. 1 (2020): 64–75. http://dx.doi.org/10.32530/jaast.v4i1.156.

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Difference and variation of leaves shape is usually used as primary identifier of the plant species. But some plants may have a similar leaf shape and thus require another more accurate identifier. This study applied principal component analysis (PCA) methods for identifying tropical plant species from the shape of the leaves. This method simplified the observed variables by reducing the dimensions of the information that is stored as much as 75%, so it did not eliminate important information and can save the data processing time. There were 100 images of leaves taken from several sides of the

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Sasaki, Yui, Daisuke Suzuki, Ryo Tokita, Hiroyuki Takashima, Hirofumi Matsumura, and Satoshi Nagoya. "Specific pelvic shape in patients with developmental dysplasia of the hip on 3D morphometric homologous model analysis." PLOS ONE 19, no. 6 (2024): e0300938. http://dx.doi.org/10.1371/journal.pone.0300938.

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Purpose To clarify the morphological factors of the pelvis in patients with developmental dysplasia of the hip (DDH), three-dimensional (3D) pelvic morphology was analyzed using a template-fitting technique. Methods Three-dimensional pelvic data of 50 patients with DDH (DDH group) and 3D pelvic data of 50 patients without obvious pelvic deformity (Normal group) were used. All patients were female. A template model was created by averaging the normal pelvises into a symmetrical and isotropic mesh. Next, 100 homologous models were generated by fitting the pelvic data of each group of patients to

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24

Sundberg, Per. "Shape and Size-Constrained Principal Components Analysis." Systematic Zoology 38, no. 2 (1989): 166. http://dx.doi.org/10.2307/2992385.

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Sundberg, P. "Shape and Size-Constrained Principal Components Analysis." Systematic Biology 38, no. 2 (1989): 166–68. http://dx.doi.org/10.1093/sysbio/38.2.166.

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26

Mahmood, Muhammad Tariq. "Shape from focus using principal component analysis in discrete wavelet transform." Optical Engineering 48, no. 5 (2009): 057203. http://dx.doi.org/10.1117/1.3130232.

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27

Akhtar, Naeem, Muhammad Idrees, Furqan Ur Rehman, Muhammad Ilyas, Qaiser Abbas, and Muhammad Luqman. "Shape and texture based classification of citrus using principal component analysis." International Journal of Agricultural Extension 9, no. 2 (2021): 229–38. https://doi.org/10.33687/ijae.009.02.3525.

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Citrus family consists of a variety of eatable, consumable and usable items with varying nutritional contents. Naked eye citrus classification needs expert human effort, which provides poor decision reliability. The unreliable classification decision may be extremely hazardous when the citrus is being classified for exports or usage in pharmacy products and various food items. In this paper, citrus fruit has been classified on shape and texture features. Principal Component Analysis (PCA) was used as a methodology to explore statistical findings. The average accuracy of the system proposed is

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Alharbi, T. "Principal Component Analysis for pulse-shape discrimination of scintillation radiation detectors." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 806 (January 2016): 240–43. http://dx.doi.org/10.1016/j.nima.2015.10.030.

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Ogah, D. M., and M. Kabir. "Variability in size and shape in muscovy duck with age: Principal component analysis." Biotehnologija u stocarstvu 29, no. 3 (2013): 493–504. http://dx.doi.org/10.2298/bah1303493o.

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Body weight and six linear body measurements, body length (BL), breast circumference (BCC), thigh length (TL), shank length (SL), total leg length (TLL) and wing length were recorded on 150 male and female muscovy ducklings and evaluated at 3, 5, 10, 15 and 20 weeks of age. Principal component analysis was used to study the dependence structure among the body measurements and to quantify sex differences in morphometric size and shape variations during growth. The first principal components at each of the five ages in both sexes accounted between 71.54 to 92.95% of the variation in the seven me

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Ogah, D. M., and M. Kabir. "Variability in size and shape in muscovy duck with age: Principal component analysis." Biotehnologija u stocarstvu 30, no. 1 (2014): 125–36. http://dx.doi.org/10.2298/bah1401125o.

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Body weight and six linear body measurements, body length (BL), breast circumference (BCC), thigh length (TL), shank length (SL), total leg length (TLL) and wing length were recorded on 150 male and female muscovy ducklings and evaluated at 3, 5, 10, 15 and 20 weeks of age. Principal component analysis was used to study the dependence structure among the body measurements and to quantify sex differences in morphometric size and shape variations during growth. The first principal components at each of the five ages in both sexes accounted between 71.54 to 92.95% of the variation in the seven me

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Mazo, Kean Roe Felipe, and Lowell Gazo Aribal. "Leaf Size Indices and Outline-Based Geomorphometric Analysis of Five Philippine Endemic Saurauia Willd. (Actinidiaceae)." Jurnal Sylva Lestari 13, no. 2 (2025): 454–66. https://doi.org/10.23960/jsl.v13i2.1139.

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Species discrimination among species of Saurauia is challenging due to large morphological variation. This study examines the intraspecific variations of the 5 Philippine endemic Saurauia species using leaf size indices (LSI) and outline-based geometric morphometrics to facilitate species discrimination. Leaf samples were measured using the traditional method, scanned, converted to binary images, subjected to elliptic Fourier Analyses, and quantitatively analyzed using principal component analysis (PCA). The leaf morphology significantly differed among species based on the results of LSI and l

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Goto, Lyè, Wonsup Lee, Toon Huysmans, Johan F. M. Molenbroek, and Richard H. M. Goossens. "The Variation in 3D Face Shapes of Dutch Children for Mask Design." Applied Sciences 11, no. 15 (2021): 6843. http://dx.doi.org/10.3390/app11156843.

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The use of 3D anthropometric data of children’s heads and faces has great potential in the development of protective gear and medical products that need to provide a close fit in order to function well. Given the lack of detailed data of this kind, the aim of this study is to map the size and shape variation of Dutch children’s heads and faces and investigate possible implications for the design of a ventilation mask. In this study, a dataset of heads and faces of 303 Dutch children aged six months to seven years consisting of traditional measurements and 3D scans were analysed. A principal co

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Kurosumi, M., and K. Mizukoshi. "Principal component analysis of three-dimensional face shape: Identifying shape features that change with age." Skin Research and Technology 24, no. 2 (2017): 213–22. http://dx.doi.org/10.1111/srt.12416.

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Yamamoto, Satoshi, Yumiko Hosoya, Norimichi Tsumura, and Keiko Ogawa-Ochiai. "Principal component analysis for dental shade color." Dental Materials 28, no. 7 (2012): 736–42. http://dx.doi.org/10.1016/j.dental.2012.03.010.

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Andrean Nugraha, Rezky, Eka Wahyu Hidayat, and Rahmi Nur Shofa. "Klasifikasi Jenis Buah Jambu Biji Menggunakan Algoritma Principal Component Analysis dan K-Nearest Neighbor." Generation Journal 7, no. 1 (2023): 1–7. http://dx.doi.org/10.29407/gj.v7i1.17900.

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The maturity level of guava fruit can be determined by looking at various factors. Shape is one of the factors that play a role in identifying certain objects. The classification of guava fruit can be seen from the shape, texture and color. The shape of the guava fruit is quite diverse ranging from round (Round shape) to oval (Pear shape). So a Matlab application was built to determine the type of guava based on its color, shape and texture. K-Nearest Neighbor can classify objects based on learning data that is closest to the object so that the results can be more accurate. Principal Component

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Liu, Kristie, David J. Greencorn, Daniel I. Aponte, Shawn M. Robbins, and David J. Pearsall. "Comparison of surrogate 50th percentile human headforms to an adult male sample using three-dimensional modeling and principal component analysis." Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology 233, no. 3 (2019): 432–42. http://dx.doi.org/10.1177/1754337119840848.

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Ice hockey helmets are required to be impact tested while mounted to a surrogate 50th percentile adult male headform. However, head shape and size can vary substantially from user to user. Furthermore, the contact area between a headform and helmet interior has been identified as an important factor affecting the protective capabilities of a helmet. The objective of this study was to compare quantitative measures of head shapes between three 50th percentile adult male headforms and a sample of adult human subjects who wore a medium-sized helmet. Using three-dimensional models of the human subj

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Baisantry, Munmun, Anil K. Sao, and Dericks Praise Shukla. "Selection of shape-preserving, discriminative bands using supervised functional principal component analysis." International Journal of Remote Sensing 43, no. 10 (2022): 3868–89. http://dx.doi.org/10.1080/01431161.2022.2105174.

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WSTANABE, Osamu, Kazuo YONEKURA, and Seiji KUBO. "1308 Study of Shape Design via Principal Component Analysis and its Optimization." Proceedings of Design & Systems Conference 2013.23 (2013): _1308–1_—_1308–7_. http://dx.doi.org/10.1299/jsmedsd.2013.23._1308-1_.

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Saleh, H., A. yahya, M. Sayed, and M. Ashour. "Pulse Shape Discrimination Techniques Based on Cross-Correlation and Principal Component Analysis." International Journal of Computer Applications 38, no. 5 (2012): 6–11. http://dx.doi.org/10.5120/4602-6804.

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Somers, Keith M. "Allometry, Isometry and Shape in Principal Components Analysis." Systematic Zoology 38, no. 2 (1989): 169. http://dx.doi.org/10.2307/2992386.

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Saykin, A. J., L. A. Flashman, T. McHugh, et al. "Principal components analysis of hippocampal shape in schizophrenia." Schizophrenia Research 60, no. 1 (2003): 206. http://dx.doi.org/10.1016/s0920-9964(03)81145-3.

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Somers, K. M. "Allometry, Isometry and Shape in Principal Components Analysis." Systematic Biology 38, no. 2 (1989): 169–73. http://dx.doi.org/10.1093/sysbio/38.2.169.

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Julianda, Rindy, Tundo, and Sugeng. "Chili Type Detection System Using Principal Component Analysis Method." International Journal Software Engineering and Computer Science (IJSECS) 5, no. 1 (2025): 102–12. https://doi.org/10.35870/ijsecs.v5i1.3735.

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Classification of types of chili vegetables is an important aspect in the agricultural industry to increase the efficiency of product management, packaging and distribution. This research aims to implement the Principal Component Analysis (PCA) method in the process of classifying vegetables and types of chilies. PCA is used to reduce the dimensionality of the data and extract the main features that are significant in distinguishing vegetable categories. The research dataset consists of digital images of chili vegetables which are extracted into color, texture and shape attributes. The researc

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Aldibaja, Mohammad Amro, and Shinichi Suzuki. "Eye Shape Detection Based on Texture Modeling in Log-Polar Domain Using Principal Component Analysis and Recurrent Neural Network." Journal of the Institute of Industrial Applications Engineers 3, no. 2 (2015): 89–95. http://dx.doi.org/10.12792/jiiae.3.89.

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Hasan, Moh Arie. "Classification of Apple Types Using Principal Component Analysis and K-Nearest Neighbor." International Journal of Information System Technology and Data Science 1, no. 1 (2023): 15–22. http://dx.doi.org/10.61398/ijist-das.v1i1.11.

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Apple is a fruit that is quite popular in Indonesia and is widely consumed by people. This fruit has various types of shapes and colors. Types of apples can be distinguished by their color, size, and shape, but it is still difficult for ordinary people to type apples that are more similar in color and size, such as the examples of Braeburn and Crimson Snow apples. This gave rise to the idea of researching image processing to classify the types of apples. This is to help determine the differences between the two types of apples. The classification process of apples is done by testing the image

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Sarma, Olympica, Mubashir Ali Rather, Syed Shahnaz, and R. S. Barwal. "Principal Component Analysis of Morphometric Traits in Kashmir Merino Sheep." Journal of Advances in Biology & Biotechnology 27, no. 9 (2024): 362–69. http://dx.doi.org/10.9734/jabb/2024/v27i91306.

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Aims: To study the principal component analysis (PCA) of morphometric traits in Kashmir Merino sheep Place and Duration of Study: Sheep Breeding Farm, Kralpathri, Kashmir, India and 2019. Methodology: This study was preformed to evaluate the morphometric traits of 518 Kashmir Merino sheep in Jammu & Kashmir under a multivariate approach. The body measurements included in the study were face length (FL), ear length (EL), ear width (EW), body length (BL), body height (BH), chest girth (CG), paunch girth (PG), tail length (TL), horn length (HL) and body weight (BW). Principal component analys

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Surya Kant Prajapati and Mrs. C.Navamani. "EFFECTIVE APPROACH FOR FACE RECOGNITION AND ACTIVE SHAPE 3D MODELS USING KERNEL PRINCIPAL COMPONENT ANALYSIS." international journal of engineering technology and management sciences 7, no. 2 (2023): 787–97. http://dx.doi.org/10.46647/ijetms.2023.v07i02.085.

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Face Recognition is a computer application that is capable of detecting, tracking, identifying or verifying human faces from an image or video captured using a digital camera. Although lot of progress has been made in domain of face detection and recognition for security, identification and surveillance purpose, but still there are issues hindering the progress to reach or surpass human level accuracy. These issues are variations in human facial appearance such as; varying lighting condition, noise in face images, scale, pose etc. Kernel principal component analysis (KPCA) as a powerful nonlin

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Köhler, Alexander, Marvin Kahra, and Michael Breuß. "A First Approach to Quantum Logical Shape Classification Framework." Mathematics 12, no. 11 (2024): 1646. http://dx.doi.org/10.3390/math12111646.

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Quantum logic is a well-structured theory, which has recently received some attention because of its fundamental relation to quantum computing. However, the complex foundation of quantum logic borrowing concepts from different branches of mathematics as well as its peculiar settings have made it a non-trivial task to devise suitable applications. This article aims to propose for the first time an approach using quantum logic in image processing for shape classification. We show how to make use of the principal component analysis to realize quantum logical propositions. In this way, we are able

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Campos, D., C. O. N. Ikeobi, O. Olowofeso, and O. F. Smith. "Multivariate principal components analysis of the morphostructural traits of West African Dwarf sheep." Nigerian Journal of Animal Production 41, no. 2 (2021): 34–43. http://dx.doi.org/10.51791/njap.v41i2.771.

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A study was conducted to determine the interdependence among conformation traits of 178 West African Dwarf sheep and to predict body weight from their independent scores using principal components analysis. Body weight and nine morphostructural traits: height at withers, body length, heart girth, rump height, hip width, chest depth, fore canon bone length, tail length, and ear length were measured. Phenotypic correlation coefficients between body weight and body dimensions ranged from 0.78 to 0.79. Anti-image correlations of the body shape characters showed that partial correlations were low.

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Signorelli, Javier H., Federico Márquez, and Guido Pastorino. "Phenotypic variation of south-western Atlantic clam Mactra isabelleana (Bivalvia: Mactridae)." Journal of the Marine Biological Association of the United Kingdom 93, no. 2 (2012): 511–17. http://dx.doi.org/10.1017/s0025315412000410.

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The phenotypic shell shape variation of Mactra isabelleana was tested using the geometric morphometric method. Four localities were sampled along the Río de la Plata estuary and the coast of Buenos Aires province. Principal component analysis and canonical variates analysis of the first principal components were performed to reveal the shell variation and differences among localities, respectively. The specimens from different microhabitats mostly overlapped, although differences in shape were observed in the development of the umbo, the enlargement of the dorsoventral axes and the elongation

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