Browsing by Author "Carrasco, Miguel"

Now showing 1 - 7 of 7
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    GDXray : The Database of X-ray Images for Nondestructive Testing
    (2015) Mery Quiroz, Domingo; Riffo, Vladimir; Zscherpel, Uwe; Mondragón, German; Lillo, Iván; Zuccar, Irene; Löbel Díaz, Hans-Albert; Carrasco, Miguel
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    Image Acquisition and Automated Inspection of Wine Bottlenecks by Tracking in Multiple Views
    (2008) Carrasco, Miguel; Pizarro, Luis; Mery Quiroz, Domingo Arturo
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    Image-Based Automated Width Measurement of Surface Cracking
    (2021) Carrasco, Miguel ; Araya-Letelier, Gerardo ; Velázquez, Ramiro ; Visconti, Paolo
    The detection of cracks is an important monitoring task in civil engineering infrastructure devoted to ensuring durability, structural safety, and integrity. It has been traditionally performed by visual inspection, and the measurement of crack width has been manually obtained with a crack-width comparator gauge (CWCG). Unfortunately, this technique is time-consuming, suffers from subjective judgement, and is error-prone due to the difficulty of ensuring a correct spatial measurement as the CWCG may not be correctly positioned in accordance with the crack orientation. Although algorithms for automatic crack detection have been developed, most of them have specifically focused on solving the segmentation problem through Deep Learning techniques failing to address the underlying problem: crack width evaluation, which is critical for the assessment of civil structures. This paper proposes a novel automated method for surface cracking width measurement based on digital image processing techniques. Our proposal consists of three stages: anisotropic smoothing, segmentation, and stabilized central points by k-means adjustment and allows the characterization of both crack width and curvature-related orientation. The method is validated by assessing the surface cracking of fiber-reinforced earthen construction materials. The preliminary results show that the proposal is robust, efficient, and highly accurate at estimating crack width in digital images. The method effectively discards false cracks and detects real ones as small as 0.15 mm width regardless of the lighting conditions.
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    Oxigenación en músculos respiratorios y locomotores durante el ejercicio máximo en doscorredores de maratón
    (2020) Contreras Briceño, Felipe; Espinosa Ramirez,Maximiliano Andres; Cerda Vasquez Francisco Ignacio; Carrasco, Miguel; Henriquez Llambias Diego Andres; Hevia Ramos, Gonzalo Benjamin; Araneda, Oscar; Viscor, Ginés
    Un elevado trabajo respiratorio (work of breathing, WOB) asociado a la hiperventilación pulmonar durante el ejercicio físico puede limitar el rendimiento deportivo en corredores de maratón. Evaluar los cambios del WOB durante el ejercicio físico máximo, como es la prueba de consumo de oxígeno (VO2-máx), permite conocer la intensidad de ejercicio a la cual el WOB limita la entrega de nutrientes y oxígeno en músculos periféricos implicados en la locomoción. La evaluación no invasiva de la saturación de oxígeno a nivel muscular (SmO2) por medio de la interpretación de ondas cercanas al rango infrarrojo (Near Infrared Spectroscopy, NIRS) es una método novedoso y útil para cuantificar el trabajo muscular, aplicable tanto en musculatura intercostal (SmO2-m.intercostales) para el WOB, como en musculatura locomotora (SmO2-m.vastus laterallis) para la carga periférica. Así, a medida que aumenta la intensidad del esfuerzo físico es esperable una mayor disminución en SmO2; sin embargo, se desconoce como la estrategia ventilatoria usada para alcanzar la hiperventilación pulmonar afecta la SmO2 de estos grupos musculares, cuyo trabajo muscular los afecta recíprocamente a través del reflejo metabólico. Como caso clínico, presentamos los cambios en SmO2-m.intercostales (WOB) y locomotora (SmO2-m.vastus laterallis) durante la prueba de VO2-máx. en dos corredores competitivos demaratón de similares características antropométricas, capacidad física, régimen de entrenamiento e historial deportivo. El objetivo es entregar nueva información que muestre cómo la estrategia ventilatoria adoptada durante el ejercicio puede limitar el trabajo muscular periférico realizado.
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    Robust automated multiple view inspection
    (2007) Pizarro, Luis; Mery Quiroz, Domingo; Delpiano Costabal, Rafael; Carrasco, Miguel
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    Visual inspection of glass bottlenecks by multiple-view analysis
    (TAYLOR & FRANCIS LTD, 2010) Carrasco, Miguel; Pizarro, Luis; Mery, Domingo
    The narrow structure of bottlenecks poses a very challenging problem for automated visual inspection systems and surprisingly, this issue has received little attention in literature. Bottleneck inspection is highly relevant to the fabrication of glass bottles, e.g., for the wine and beer industry. Defects in glass bottles can arise in various situations such as an incomplete reaction in a batch, batch contaminants and interactions of the melted material among others. This paper presents an inspection approach that utilises geometry of multiple views along with a rich set of feature descriptors to discriminate real flaws from false alarms in uncalibrated images of glass bottlenecks. The proposed method is based on an automatic multiple view inspection (AMVI) technique for the automatic detection of flaws. This technique involves an initial step that extracts numerous segmented regions from a set of views of the object under inspection. These regions are subsequently classified either as real flaws or as false alarms. The classification process considers that image noise and false alarms occur as random events in different views while real flaws induce geometric and featural relations in the views where they appear. Therefore, by analysing such relations it is possible to successfully localise real flaws and to discard a large number of false alarms. An important characteristic of the proposed methodology is the complete lack of camera calibration which makes our method very suitable for applications where camera calibration is difficult or expensive to carry out. Our inspection system achieves a true positive rate of 99.1% and a false positive rate of 0.9%.