Cast shadow modelling and detection

Computer vision applications are often confronted by the need to differentiate between objects and their shadows. A number of shadow detection algorithms have been proposed in literature, based on physical, geometrical, and other heuristic techniques. While most of these existing approaches are dependent on the scene environments and object types, the ones that are not, are classified as superior to others conceptually and in terms of accuracy. Despite these efforts, the design of a generic, accurate, simple, and efficient shadow detection algorithm still remains an open problem. In this thesis, based on a physically-derived hypothesis for shadow identification, novel, multi-domain shadow detection algorithms are proposed and tested in the spatial and transform domains. A novel "Affine Shadow Test Hypothesis" has been proposed, derived, and validated across multiple environments. Based on that, several new shadow detection algorithms have been proposed and modelled for short-duration video sequences, where a background frame is available as a reliable reference, and for long duration video sequences, where the use of a dedicated background frame is unreliable. Finally, additional algorithms have been proposed to detect shadows in still images, where the use of a separate background frame is not possible. In this approach, the author shows that the proposed algorithms are capable of detecting cast, and self shadows simultaneously. All proposed algorithms have been modelled, and tested to detect shadows in the spatial (pixel) and transform (frequency) domains and are compared against state-of-art approaches, using popular test and novel videos, covering a wide range of test conditions. It is shown that the proposed algorithms outperform most existing methods and effectively detect different types of shadows under various lighting and environmental conditions

Medical image enhancement

Each image acquired from a medical imaging system is often part of a two-dimensional (2-D) image set whose total presents a three-dimensional (3-D) object for diagnosis. Unfortunately, sometimes these images are of poor quality. These distortions cause an inadequate object-of-interest presentation, which can result in inaccurate image analysis. Blurring is considered a serious problem. Therefore, “deblurring” an image to obtain better quality is an important issue in medical image processing. In our research, the image is initially decomposed. Contrast improvement is achieved by modifying the coefficients obtained from the decomposed image. Small coefficient values represent subtle details and are amplified to improve the visibility of the corresponding details. The stronger image density variations make a major contribution to the overall dynamic range, and have large coefficient values. These values can be reduced without much information loss

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Automatic Image Shadow Identification using LPF in Homomorphic Processing System

Abstract. In this paper, we have used homomorphic system and HSV color space for shadow detection. Here, we have defined a LPF to detect the shadow over a dark object on the background. In this case, we omit the phase information in order not to emphasize the reflection component. Furthermore, the presented experimental results which are obtained for shadow identification, show the efficiency of the proposed method

Desarrollo y validación de un modelo dinámico para una pila de combustible tipo PEM

JORNADAS DE AUTOMÁTICA (27) (27.2006.ALMERÍA)El objetivo de este trabajo es realizar un modelo dinámico detallado de una pila de combustible tipo PEM de 1.2 kW de potencia nominal. El modelo desarrollado incluye efectos como el ’flooding’ y la dinámica de la temperatura y es de utilidad para poder diseñar y ensayar controles tanto de la válvula de purga como de la refrigeración de la pila mediante un ventilador. Se ha desarrollado un novedoso tratamiento de la ecuación experimental que modela la curva de polarización que simplifica considerablemente su caracterización. Por último el modelo realizado ha sido validado con datos tomados de una pila real