Publications

@article{barreiro_operator_nodate,

title = {Operator and analyst interfaces for monitoring of wear in tool inserts},

author = {Joaquín Barreiro and Alberto Sanz and LK Hernández and Enrique Alegre and Manuel Castejón-Limas},

url = {https://d1wqtxts1xzle7.cloudfront.net/47455745/Operator_and_analyst_interfaces_for_moni20160723-29317-10pmzkk-libre.pdf?1469286941=&response-content-disposition=inline%3B+filename%3DOperator_and_analyst_interfaces_for_moni.pdf&Expires=1739527854&Signature=RWcL6iwivos9e0wdZGv2op4N17pTROrpur~Yrv~yUJp2ta5PuCsKYNk-gnEyq2hojbariQ5iVTq7oPhutXCpZHCk5x~oE5Z~mH5mTrzcuxUCRwc4hRZlUY~HlJbpBLtJDTKagp2VLdb2UYRaqWMREe4VwJnMKyW8DjlgQtY4NiMx8ECM6FWcANQUhPZmRvT2RLYKEYbI9NMLGaW4qs9FTGATkhPSmkFJ6nt6QJQ4VkGmn55XlN3gE7hYbUDGTr6oZ7LzpBlvKWq856FUqSPD2Uy6Wz0~oQ8NyZM9ynDMGOSEyu640BiwmmSWfvHOuEv9mIkoFy95Kyx9lrf73kSs5A__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA},

abstract = {Computer vision techniques have advanced significantly, enabling their effective application in industrial environments. This paper presents graphical interfaces for operators and analysts to monitor tool inserts during steel turning. The system integrates computer vision with classification techniques based on statistical moments and region descriptors, enhancing inspection and control processes.},

keywords = {Classification, Computer vision, descriptors, monitoring tool life},

pubstate = {published},

tppubtype = {article}

}

@article{suarez_pdf_nodate,

title = {PDF OFF-PRINTS},

author = {S Suárez and Enrique Alegre and Joaquín Barreiro and Patricia Morala-Arguello and Víctor González-Castro},

url = {https://www.researchgate.net/profile/J-Barreiro/publication/235792932_Classification_and_correlation_of_surface_roughness_in_metallic_parts_using_texture_descriptors/links/09e415138dec0b3b71000000/Classification-and-correlation-of-surface-roughness-in-metallic-parts-using-texture-descriptors.pdf},

abstract = {This paper presents a method for classifying surface roughness in machined metallic parts using an artificial vision system. Two texture analysis methods, GLCM and Laws' energy method, are used as descriptors. Classification is performed using LDA, QDA, and ANN, with the best results (94.23%) achieved using Neural Networks. The method successfully correlates texture descriptors with average roughness (Ra).},

keywords = {co-occurrence matrix, laws, roughness, surface texture},

pubstate = {published},

tppubtype = {article}

}

@article{garcia-olalla_tool_nodate,

title = {Tool wear classification using texture descriptors based on Local Binary Pattern},

author = {Óscar García-Olalla Olivera and Enrique Alegre and Joaquín Barreiro and Laura Fernández-Robles and María Teresa García-Ordás},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=en&user=opCbArQAAAAJ&cstart=100&pagesize=100&sortby=title&citation_for_view=opCbArQAAAAJ:RHpTSmoSYBkC},

abstract = {This paper presents a new approach for tool wear identification in metal milling using texture descriptors LBP and ALBP, enhanced with LOSIB (Local Oriented Statistical Information Booster). Two datasets are considered: Cutting Edges (gray-scale images of worn cutting edges) and Edge Wear (cropped worn areas). Both datasets are labeled into two (low/high wear) and three (low/medium/high wear) classes. Classification using Support Vector Machine with Least Squares training achieved a 74.05% accuracy for two classes and 53.77% for three classes in the Edge Wear dataset.},

keywords = {Machine Learing, Manufacturing, SVM, texture analysis, Tool wear},

pubstate = {published},

tppubtype = {article}

}

@article{martinez_san_martin_segmentation_nodate,

title = {A segmentation approach for evaluating wear of inserts in milling machines with computer vision techniques},

author = {Guillermo Martínez San Martín and Laura Fernández-Robles and Enrique Alegre and Óscar García-Olalla Olivera},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=es&user=4jZgNVkAAAAJ&sortby=title&citation_for_view=4jZgNVkAAAAJ:Se3iqnhoufwC},

abstract = {Measuring tool wear in milling machines is an important task to evaluate the lifetime of the cutting parts (inserts) and deciding whether we should replace them. In our research, we propose to use computer vision algorithms to perform this task. Part of the research is to evaluate the accuracy of different segmentation algorithms that segment the area of wear. We have used two methods: k-Means and Mean Shift. To evaluate the segmentation results the Dice coefficient was used, obtaining with Mean Shift a QS= 0.5923 for all the edges and a QS= 0.6831 just for edges with high wear.},

keywords = {Computer vision, milling machines, segmentation, Tool wear},

pubstate = {published},

tppubtype = {article}

}

@article{gonzalez-castro_adaptive_nodate,

title = {Adaptive texture description for semen vitality assessment},

author = {Víctor González-Castro and Enrique Alegre and Alexci Suárez-Castrillón and Óscar García-Olalla Olivera and María Teresa García-Ordás},

url = {https://d1wqtxts1xzle7.cloudfront.net/47501584/Adaptive_texture_description_for_semen_v20160725-8795-17ysl7b-libre.pdf?1469454941=&response-content-disposition=inline%3B+filename%3DAdaptive_texture_description_for_semen_v.pdf&Expires=1739193493&Signature=SPojfSyGRHX-PAT8i5lgMywJ52650XScp8t74YrAAbRnnZ0mPJbvVLYRGRVG3eNTcH0gHbWwIshfAz3ok9lb8gwRdrSSDSazEnRN5cYx8eBGm1rhAQ0WmI7Cwc0TaLMt1nk41LMRM4hROUQEF9P6YZShfswvVnj~e9IXqGrjksaOYlzuk7Y2zsIzg4jnkgk~w1gJeZ-gxUj~5mdtEESX7zDTdTrbyvs4Roiyoig8~jgMdtkCptWrABzqnovahSK9D-vjedWjo-EVaVue22Wa-k1z7hSSerV1X~AZt68BQqa2GqhwOxQ~qfJdpU4j8o88~hi6RcbTtsGj7-BE9vyWZA__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA},

abstract = {In this paper an adaptive texture description method based on granulometry 

is proposed. It is a variant of the Pattern Spectrum, and both the adaptive 

and the ordinary descriptors are used to classify boar spermatozoa into 

dead or alive. A set of 845 boar spermatozoon heads were assessed and a 

back-propagation neural network was used in order to classify them. We 

have described both the original grey level images and the same images 

after applying a range texture filter on them. The best hit rates have been 

obtained when the adaptive Pattern Spectrum was used to describe the 

filtered images.},

keywords = {boar semen, granulometry, pattern spectrum, texture description},

pubstate = {published},

tppubtype = {article}

}

@article{fernandez-robles_svm_nodate,

title = {SVM APPROACH TO CLASSIFY BOAR ACROSOME INTEGRITY OF A MULTI-FEATURES SURF},

author = {Laura Fernández-Robles and Óscar García-Olalla Olivera and María Teresa García-Ordás and Diego García-Ordás and Enrique Alegre},

url = {https://d1wqtxts1xzle7.cloudfront.net/44449818/SVM_approach_to_classify_boar_acrosome_i20160405-28158-qszl8d-libre.pdf?1459894369=&response-content-disposition=inline%3B+filename%3DSVM_Approach_to_Classify_Boar_Acrosome_I.pdf&Expires=1739795517&Signature=Tgnu3YoKmzyQiRloeYT95Z4ufJAMUtL~2z~sVtWh4x0OwtjsDwwxq7cUYjl-q5NxrhAJJNz3b7f7YchGOHb6p7lf48EUqtmL1Cjm1mI6YY59k3-ds8J53mCRa0SdXtjjZa0MvchGa2Aqbqx3pt5Ep6v5To7Trx3aKfElmzjdaSP7yKZxPa~b92YaH02HFDTQkx8UFEf6TuCoitK-mz4On4xw-6-RfHwdh37FtKePaXdKxv~sHwmvwVWlOn~yaNIPTO1sl3X8LT9zuUU~8yHltm8xUlFuOzWXwgAe8bMmYMWr6HwY-GG7ExpJQj43FmIa6XXflt7MlJRIuAzSgSo~Lw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA},

abstract = {This paper presents an approach to improve the classification of invariant local feature descriptors in images of boar spermatozoa heads using Support Vector Machine (SVM). The method involves detecting interest points with SURF and classifying the acrosome as intact or damaged. The approach focuses on classifying the whole head rather than individual points, leveraging the fact that a head typically has more distinctive points of its own class than doubtful ones. The results show a hit rate of 90.91%, indicating that this method could be an effective alternative for classifying invariant local features.},

keywords = {Image classification, Image Recognition, Invariant Local Features, support vector machine, SURF},

pubstate = {published},

tppubtype = {article}

}

@article{lopez_de_celis_evaluation_nodate,

title = {An evaluation of Cascade Object Detector and Support Vector Machine methods for People Detection using a RGB-Depth camera located in a zenithal position},

author = {Eduardo López de Celis and Óscar García-Olalla Olivera and Maite García-Ordás and Enrique Alegre},

url = {https://www.ehu.eus/documents/3444171/4484752/61.pdf},

abstract = {This project solves the problem of people detection 

using an RGB-Depth camera from a zenithal 

position. The detection process has been 

implemented for binary (head – no head) and 

multiclass approaches (short hair head, long hair 

head, ponytail and shoulders-no head). For this task, 

Histogram of Oriented Gradients (HOG) 

demonstrates to be a better feature descriptor than 

Local Binary Patterns (LBP). In the classification 

step, two models have been evaluated: SVM and 

Cascade Object Detector. Our experiments shown 

the better performance of SVM.},

keywords = {Cascade Object Detector, head detection, Histogram of Oriented Gradients, Local Binary Patterns, support vector machine},

pubstate = {published},

tppubtype = {article}

}

@article{de_paz_centeno_design_nodate,

title = {DESIGN AND IMPLEMENTATION OF BRPY: A BIORECOGNITION SYSTEM (FACE DETECTION AND RECOGNITION, AGE ESTIMATION AND GENDER ESTIMATION) BASED ON THE FACE.},

author = {Iván Paz Centeno and Eduardo Fidalgo and Óscar García-Olalla Olivera and Enrique Alegre},

url = {https://www.ehu.eus/documents/3444171/4484752/108.pdf},

journal = {Power},

volume = {5},

pages = {2A},

abstract = {This document outlines the design and implementation of BRPY, an open-source multi-platform program for real-time face detection, recognition, and age and gender estimation. Developed in Python and C++ using OpenBR and OpenCV, it focuses on using the ODroid U3 platform for execution and details the design of the program interface.},

keywords = {Age Estimation, Algorithm, BRPY, Detection, Face, Gender Estimation, OpenBR, Python, Recognition},

pubstate = {published},

tppubtype = {article}

}

@article{gonzalez-castro_design_nodate,

title = {DESIGN AND IMPLEMENTATION OF AN EMBEDDED SYSTEM FOR IMAGE ACQUISITION OF INSERTS IN A HEADTOOL MACHINE},

author = {Víctor González-Castro and Laura Fernández-Robles and Enrique Alegre},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=en&user=4jZgNVkAAAAJ&cstart=20&pagesize=80&sortby=title&citation_for_view=4jZgNVkAAAAJ:WF5omc3nYNoC},

abstract = {Based on the idea of combining embedded systems, industrial cameras and image processing, in this paper we present the design of an embedded and portable image acquisition system on a Raspberry PI 2 and other in a notebook. The image acquisition system has been developed using two different programming languages, such as Python and C++. The OpenCV Computer Vision library, in its new 3.0. 0 version was used to carry out all the computer vision processing.},

keywords = {Embedded Systems, Image Acquisition, OpenCV, Raspberry Pi},

pubstate = {published},

tppubtype = {article}

}

@article{alonso_estructuracion_nodate,

title = {ESTRUCTURACIÓN GRÁFICA DE LA ELECTRÓNICA MEDIANTE},

author = {Ángel Alonso and M Ferrero and C Redondo and Enrique Alegre and FJ Rodríguez},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=es&user=opCbArQAAAAJ&cstart=20&pagesize=80&sortby=title&citation_for_view=opCbArQAAAAJ:ldfaerwXgEUC},

abstract = {Este trabajo tiene como objetivo demostrar que el uso de una sintaxis gráfica potencia la eficacia didáctica de los sistemas multimedia aplicados a la enseñanza de la electrónica. Se propone integrar el texto dentro de una gramática gráfica, permitiendo al autor decidir el uso de expresiones textuales según sea necesario. De esta manera, las pantallas del ordenador presentarán un enfoque visual, con poco texto, muchas animaciones y la opción de explicaciones verbales para cada conjunto gráfico, favoreciendo un aprendizaje más interactivo y visual.},

keywords = {Animaciones, Estructuración Gráfica, Sistemas Multimedia},

pubstate = {published},

tppubtype = {article}

}

@article{mazo_ontologihistologica_nodate,

title = {Ontología Histológica del Sistema Cardiovascular Humano},

author = {Claudia Mazo and Liliana Salazar and María Trujillo and Óscar Corcho and Enrique Alegre},

url = {https://www.researchgate.net/profile/Claudia-Mazo/publication/324476993_Ontologia_Histologica_del_Sistema_Cardiovascular_Humano/links/5acf4163aca2723a3344e4d1/Ontologia-Histologica-del-Sistema-Cardiovascular-Humano.pdf},

abstract = {El uso inconsistente del vocabulario en las ciencias morfológicas genera ambigüedad y subjetividad, afectando la investigación y recuperación de información. Los Simposios Ibero-Latinoamericanos de Terminología (SILAT) analizan y difunden la terminología morfológica internacional para estandarizar su uso en instituciones de medicina y salud de habla hispana y portuguesa.},

keywords = {ciencias de la salud, estandarización lingüistica, SILAT, terminología morfológica},

pubstate = {published},

tppubtype = {article}

}

@article{suarez-castrillon_evaluacion_nodate,

title = {Evaluación de diferentes tipos de iluminación para la clasificación de la rugosidad de piezas metálicas mediante análisis de imagen},

author = {Alexci Suárez-Castrillón and Enrique Alegre and Patricia Morala-Argüello and Joaquín Barreiro and Víctor González-Castro},

url = {https://buleria.unileon.es/handle/10612/10344},

abstract = {Este estudio clasifica la rugosidad de piezas metálicas en procesos de torneado mediante análisis de imagen y evalúa la influencia del ángulo de iluminación. Se emplean cuatro descriptores de primer orden (media, desviación estándar, asimetría y kurtosis) y el clasificador KNN. Se analizaron 284 imágenes, comparando los resultados con métodos tradicionales. Los errores obtenidos fueron: coaxial 0.70%, angular 9.68% y rasante 1.03%. Los resultados destacan la importancia de la iluminación en la medición de la rugosidad y la efectividad de los descriptores de textura.},

keywords = {Angular, Coaxial, Descriptores de Textura, Iluminación, Inspección, kNN, Rasante, Rugosidad},

pubstate = {published},

tppubtype = {article}

}

@article{alaiz-rodriguez_use_nodate,

title = {Use of contour signatures and classification methods to optimize the tool life in metal machining; pp. 3–12},

author = {Rocío Alaiz-Rodríguez and Enrique Alegre and Joaquín Barreiro and Jonatan Ruiz},

url = {https://kirj.ee/estonian-journal-of-engineering-publications/?filter%5Byear%5D=2009&filter%5Bissue%5D=68&filter%5Bpublication%5D=464&v=04c19fa1e772},

abstract = {Tool replacement operations have a great influence over the cost of machined parts. At present, the common criteria used to determine the tool life do not optimize the use of tools and lead to significant economic losses. The main objective of this work is to define a new procedure to improve the decision about the time for tool replacement. The approach followed is based on digital images of the cutting edge that has already been explored in the literature. The novelty of the present work relies on the use of contour signatures of the wear region as the input to two techniques of classification, k-nearest neighbour and a neural network. The influence of the signature size vector is also analysed. A total of 1383 flank wear images were acquired and the error rate estimation was about 5%.},

keywords = {Classification Techniques, Digital Imaging, Flank Wear, Tool Replacement},

pubstate = {published},

tppubtype = {article}

}

@article{gangwara_triple-biggan_nodate,

title = {Triple-BigGAN: A Semi-Supervised GAN for Image synthesis and classification applied to detect facial sexual expressions},

author = {Abhishek Gangwar and Víctor González-Castro and Enrique Alegre and Eduardo Fidalgo},

url = {https://www.researchgate.net/profile/Eduardo-Fidalgo-4/publication/367056606_Triple-BigGAN_Semi-supervised_Generative_Adversarial_Networks_for_Image_Synthesis_and_Classification_on_Sexual_Facial_Expression_Recognition/links/63c54588d9fb5967c2e00368/Triple-BigGAN-Semi-supervised-Generative-Adversarial-Networks-for-Image-Synthesis-and-Classification-on-Sexual-Facial-Expression-Recognition.pdf},

keywords = {deep learning, Emotion Detection, Facial Expressions, Not Safe For Work, NSFW, Obscene Image Retrieval, Pornography},

pubstate = {published},

tppubtype = {article}

}

@article{alegre_estimacion_nodate,

title = {Estimación de la edad a partir del rostro para detectar personas con necesidades especiales de asistencia},

author = {Enrique Alegre},

url = {https://buleria.unileon.es/handle/10612/3112},

abstract = {Estimación de la edad a partir del rostro para detectar personas con necesidades especiales de asistencia“, Enrique Alegre Gutiérrez},

keywords = {Envejecimiento, Estimación de la Edad, Necesidades Especiales de Asistencia, Rostro},

pubstate = {published},

tppubtype = {article}

}

@article{morala-arguello_surface_nodate,

title = {SURFACE ROUGHNESS CLASSIFICATION IN METALLIC PARTS USING HARALICK DESCRIPTORS AND QUADRATIC DISCRIMINANT ANALYSIS},

author = {Patricia Morala-Argüello and Laura Fernández-Robles},

url = {https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2010/23374_Symp_1_head.pdf},

abstract = {An artificial vision system has been used to classify 

metallic work-parts in base of their surface roughness. 

Haralick features have been computed through the gray-level 

co-occurrence matrix (GLCM) to analyze the texture of the 

parts. Quadratic and Linear Discriminant Analysis (QDA and 

LDA) algorithms have been worked out to classify the 

descriptors. Results have proved the validity of this method to 

classify metallic parts in two classes achieving hit rates of 

97,4% using QDA.},

keywords = {Co-ocurrence Matrix, discriminantAnalysis, Haralick, roughness, surface texture},

pubstate = {published},

tppubtype = {article}

}

@article{fidalgo_evaluation_nodate,

title = {EVALUATION OF SHAPE AND COLOR DESCRIPTORS BY USING BAG OF WORD TECHNIQUES WITH ONE VS ALL CLASSIFICATION},

author = {Eduardo Fidalgo and Laura Fernández-Robles and Maite García-Ordás and Óscar García-Olalla Olivera and Enrique Alegre},

url = {https://www.researchgate.net/profile/Eduardo-Fidalgo-4/publication/257758029_Evaluation_of_shape_and_color_descriptors_by_using_bag_of_Word_techniques_with_one_vs_all_classification/links/5a2032d8458515341c85589a/Evaluation-of-shape-and-color-descriptors-by-using-bag-of-Word-techniques-with-one-vs-all-classification.pdf},

abstract = {This paper evaluates various shape and color descriptors on two datasets: “Soccer” and a newly introduced one called “Karinas_Dataset1.” Images are represented using descriptors created through the Bag of Words (BoW) technique. A one-vs-all classifier is then trained and tested with random images from the datasets. To avoid outliers, experiments are repeated 10 times and the average result is reported.},

keywords = {Bag of Words, Color Descriptors, One-vs-all, Shape Description},

pubstate = {published},

tppubtype = {article}

}

@article{fidalgo_evaluation_nodate-1,

title = {EVALUATION OF SEGMENTATION METHODS APPLIED TO INTACT AND DAMAGED BOAR SPERMATOZOON HEADS},

author = {Eduardo Fidalgo and Javier Pedro and Laura Fernández-Robles and María Teresa García-Ordás and Enrique Alegre},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=es&user=4jZgNVkAAAAJ&cstart=20&pagesize=80&sortby=title&citation_for_view=4jZgNVkAAAAJ:SeFeTyx0c_EC},

abstract = {This paper proposes evaluating four different segmentation methods using the Haussdorf distance. Although the resulting images from these methods are not uniform, several pre-processing tasks were performed to make them suitable for the evaluation. All methods were applied to the same dataset of intact and damaged spermatozoa. The evaluation compares the results of the different methods against an expert segmentation of the dataset.},

keywords = {Evaluation Methods, Haussdorf Distance, Image Pre-processing, Segmentation Methods, Spermatozoa},

pubstate = {published},

tppubtype = {article}

}

@article{bastante-ceca_pablo_nodate,

title = {Pablo Aragonés-Beltrán},

author = {María José Bastante-Ceca and María Dolores Bovea-Edo and Salvador Capuz-Rizo and Diego Carmona-Fernández and Manuel Castejón-Limas and Javier Alfonso-Cendón and Alberto Cerezo-Narváez and Ginés Delgado-Calín and Laura Fernández-Robles and Catherin Girón-Escobar},

url = {https://www.torrossa.com/en/resources/an/4648879#page=282},

journal = {Herramientas y experiencias para la evaluación por competencias en Dirección de Proyectos},

pages = {282},

keywords = {},

pubstate = {published},

tppubtype = {article}

}