Video Image Enhancement and Machine Learning Pipeline for Underwater Animal Detection and Classification at Cabled Observatories

Corrección de una afiliación en Sensors 2023, 23, 16. https://doi.org/10.3390/s23010016An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, encompassing both biotic and abiotic variables, and describing the ecological dynamics of the observed species. In this context, imaging devices are valuable tools that complement other biological and oceanographic monitoring devices. Nevertheless, large amounts of images or movies cannot all be manually processed, and autonomous routines for recognizing the relevant content, classification, and tagging are urgently needed. In this work, we propose a pipeline for the analysis of visual data that integrates video/image annotation tools for defining, training, and validation of datasets with video/image enhancement and machine and deep learning approaches. Such a pipeline is required to achieve good performance in the recognition and classification tasks of mobile and sessile megafauna, in order to obtain integrated information on spatial distribution and temporal dynamics. A prototype implementation of the analysis pipeline is provided in the context of deep-sea videos taken by one of the fixed cameras at the LoVe Ocean Observatory network of Lofoten Islands (Norway) at 260 m depth, in the Barents Sea, which has shown good classification results on an independent test dataset with an accuracy value of 76.18% and an area under the curve (AUC) value of 87.59%.This work was developed within the framework of the Tecnoterra (ICM-CSIC/UPC) and the following project activities: ARIM (Autonomous Robotic Sea-Floor Infrastructure for Benthopelagic Monitoring; MarTERA ERA-Net Cofound) and RESBIO (TEC2017-87861-R; Ministerio de Ciencia, Innovación y Universidades)

Foundations of computer vision: computational geometry, visual image structures and object shape detection

This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and first year graduate students in Engineering, Computer Science or Applied Mathematics. It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes

Test bench for mechanical characterization in reliability testing

The objective of this project isto design an ‘automatic photography bench’ for reliability validations (mechanical stress tests, chemical tests, climatic tests...) of Telematic Control Units (TCUs) atthe company Ficosa A.C., both at softwareand hardwarelevels.For each test sample, after each test, 6 photos must be taken from the 6 sides of a cube,in order to detect cracks and other defectsproduced as a result of thesereliability tests. So far,thisprocess was done manually,by laboratory technicians, which made the company waste money in each validation, so the process needed to be automatized.In order to automatize this project, a device called “PhotoBench” has been designed and tested. It has six USB cameras, a cube-like structureto support them,with reflective panels and innerlighting, and connects to the laboratory technicians’ laptop or Raspberry Pi 3 through a USB HUB. An application with a fast and easy graphical user interface(GUI), programmed in Python and wxPython,lets the user control the PhotoBenchcomfortably.Three design releases of the PhotoBench have been delivered with this project. The first one, designed experimentally by agreeing design parameters with laboratorytechnicians “by trial-and-error”and physically built as a prototype; the second one, designed through optics calculations as a proposedimprovement ofthe first release without changing the already built prototype structure; the third and last one, redesigned completely through optics calculationsas a proposed improvementto optimize the mechanical structureand image qualityfor a given high-megapixel USB camera.This way, the project’s objective has beensuccessfully fulfilled, with all threereleases being directly usable in real reliability validations atFicosa A.C. The application and the GUI let the user comfortably control the PhotoBench and remarkably reduce validation process times, showing to be a profitable investment for the company. Second and third releases werenot fullyphysicallyimplemented, but they are already being manufactured,or planned to do soin the near future.Other business units, who produceother products like mirrors or electric car componentsat Ficosa,have also shown interest in using this project’s result, as they have thesameinefficiencyproblem with reliability validatio

Computer analysis of ultrasound images of thyroid nodules, focusing on their sonographic features and cytological findings.

Ultrazvukové zobrazování patří mezi základní vyšetření uzlů ve štítné žláze, na jejichž základě se rozhoduje, zda pacient podstoupí cytologické vyšetření, které je hlavním podkladem pro rozhodování o případném chirurgickém odstranění štítné žlázy. Cytologické vyšetření má ale bohužel omezenou specificitu a případná operace s sebou nese rizika. Proto jsou hledány další metody, které by byly schopny vnést do diagnostiky více jistoty. Jednou z nových metod je počítačová podpora diagnostiky (CAD), která pomocí analýzy obrazu a strojového učení vykazuje poměrně slibné výsledky. V této práci představujeme dva do určité míry podobné, přesto však odlišné, CAD přístupy. První přístup spočívá v analýze celých uzlů pomocí Segmentation Based Fractal Texture Analysis (SFTA) algoritmu, který rozkládá obraz na jednotlivá šedotónová pásma pomocí metody binární stack-dekompozice. Pomocí tohoto přístupu bylo na datovém souboru 40 snímků hodnocených metodou křížové validace dosaženo přesnosti 92,5 % při použití náhodných lesů a 95 % při použití support vector machines (SVM). Druhý CAD přístup vychází také z metody vícenásobného prahování obrazu, ale s tím rozdílem, že z jednotlivých šedotónových pásem je extrahováno větší množství prediktorů popisujících binární texturu a dále pak, že analýza neprobíhá na uzlu jako celku, ale...Ultrasound imaging is one of the fundamental examinations of thyroid nodules, determining whether a patient undergoes a cytological examination, which is essential for the decision on a possible thyroid surgery. Unfortunately, the cytological examination has limited specificity and potential surgery carries risks. Therefore, other diagnostic methods are being sought with hope that they will be able to bring more certainty into diagnostics. One of the new methods is computer-aided diagnosis (CAD), which exhibits promising results using image analysis and machine learning. In this study, we present two somewhat similar, yet different, CAD approaches. The first approach is based on analysing entire nodules using a Segmentation Based Fractal Texture Analysis (SFTA) algorithm that splits the image into individual grayscale bands. Using this approach, we have achieved an accuracy of 92.4% using random forests (RF) and 95% using support vector machines (SVM) on a data set of 40 images evaluated by the cross-validation method. The second CAD approach is also based on the method of multiple image thresholding, but the difference is, that a larger number of predictors describing the binary texture are extracted from the individual grayscale bands. Furthermore, the analysis did not take place on whole nodules, but on...Institute of Biophysics and Informatics First Faculty of Medicine Charles UniversityÚstav biofyziky a informatiky 1. LF UK1. lékařská fakultaFirst Faculty of Medicin

Control visual de un brazo manipulador con 7GDL, en base a visión monocular, para el seguimiento de objetivos

La necesidad de incrementar la producción de las grandes empresas en la Primera Revolución Industrial permitió el desarrollo de nuevas máquinas, tecnologías y actividades, configurando el entorno perfecto para la aplicación de máquinas y procedimientos autónomos como los brazos manipuladores. En la última década se han ampliado las actividades que realizan los brazos manipuladores a diversas áreas como rescate, medicina e industria aeroespacial. La principal tarea de un brazo manipulador es alcanzar un objetivo por medio de sus elementos perceptivos. Esta tarea conlleva escoger los sensores necesarios para percibir el mundo tomando en cuenta el costo, el peso y el espacio. En esta investigación se dará solución a este problema con el uso de un sensor de visión, es decir una cámara. El mecanismo de control que se presenta se basa en dividir el movimiento tridimensional en dos movimientos sobre dos planos: Uno de estos planos es el mismo que el plano de la cámara (plano XY ) y el otro plano será perpendicular al primero y se refiere a la profundidad (plano XZ). El movimiento del objetivo en el plano de la cámara será calculado por medio del flujo óptico, es decir la traslación del objetivo del tiempo t al t + 1 en el plano XY . En cambio, el movimiento en el plano de la profundidad se estimará mediante el filtro de Kalman usando las variaciones de la traslación obtenida del flujo óptico y de la rotación dada por la matriz de cinemática directa. Finalmente, el movimiento planificado en cada plano se ejecutará de forma intercalada infinitesimalmente, obteniendo así un movimiento continuo para los tres ejes coordenados (XY Z). Los resultados experimentales obtenidos, han demostrado que se realiza un camino limpio y suavizado. Se han llevado a cabo pruebas con diferentes intensidades de iluminación, mostrando un error promedio de la trayectoria de movimiento de µx,y,z = 5.05, 4.80, 3.0 en centímetros con iluminación constante, por lo que se tiene una desviación estándar σx,y,z = 2.21, 2.77, 1.45 en centímetros. Al obtener resultados satisfactorios en las pruebas elaboradas. Se puede concluir que es posible solucionar el problema del movimiento tridimensional de un brazo manipulador dividiéndolo en dos sub-problemas que trabajan en planos perpendiculares. Esta solución nos proporciona una trayectoria suave, ya que el mecanismo de control se realiza en cada instante de tiempo obteniendo un movimiento natural.Tesi

31th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems.The amount and complexity of information itself, the number of abstractionlevels of information, and the size of databases and knowledge bases arecontinuously growing. Conceptual modelling is one of the sub-areas ofinformation modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers