3 resultados para OpenCV Computer Vision Object Detection Automatic Counting
em Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal
Resumo:
Humans can perceive three dimension, our world is three dimensional and it is becoming increasingly digital too. We have the need to capture and preserve our existence in digital means perhaps due to our own mortality. We have also the need to reproduce objects or create small identical objects to prototype, test or study them. Some objects have been lost through time and are only accessible through old photographs. With robust model generation from photographs we can use one of the biggest human data sets and reproduce real world objects digitally and physically with printers. What is the current state of development in three dimensional reconstruction through photographs both in the commercial world and in the open source world? And what tools are available for a developer to build his own reconstruction software? To answer these questions several pieces of software were tested, from full commercial software packages to open source small projects, including libraries aimed at computer vision. To bring to the real world the 3D models a 3D printer was built, tested and analyzed, its problems and weaknesses evaluated. Lastly using a computer vision library a small software with limited capabilities was developed.
Resumo:
Computer vision is a field that uses techniques to acquire, process, analyze and understand images from the real world in order to produce numeric or symbolic information in the form of decisions [1]. This project aims to use computer vision to prepare an app to analyze a Madeira Wine and characterize it (identify its variety) by its color. Dry or sweet wines, young or old wines have a specific color. It uses techniques to compare histograms in order to analyze the images taken from a test sample inside a special container designed for this purpose. The color analysis from a wine sample using an image captured by a smartphone can be difficult. Many factors affect the captured image such as, light conditions, the background of the sample container due to the many positions the photo can be taken (different to capture facing a white wall or facing the floor for example). Using new technologies such as 3D printing it was possible to create a prototype that aims to control the effect of those external factors on the captured image. The results for this experiment are good indicators for future works. Although it’s necessary to do more tests, the first tests had a success rate of 80% to 90% of correct results. This report documents the development of this project and all the techniques and steps required to execute the tests.
Resumo:
Nowadays, more than half of the computer development projects fail to meet the final users' expectations. One of the main causes is insufficient knowledge about the organization of the enterprise to be supported by the respective information system. The DEMO methodology (Design and Engineering Methodology for Organizations) has been proved as a well-defined method to specify, through models and diagrams, the essence of any organization at a high level of abstraction. However, this methodology is platform implementation independent, lacking the possibility of saving and propagating possible changes from the organization models to the implemented software, in a runtime environment. The Universal Enterprise Adaptive Object Model (UEAOM) is a conceptual schema being used as a basis for a wiki system, to allow the modeling of any organization, independent of its implementation, as well as the previously mentioned change propagation in a runtime environment. Based on DEMO and UEAOM, this project aims to develop efficient and standardized methods, to enable an automatic conversion of DEMO Ontological Models, based on UEAOM specification into BPMN (Business Process Model and Notation) models of processes, using clear semantics, without ambiguities, in order to facilitate the creation of processes, almost ready for being executed on workflow systems that support BPMN.