26 research outputs found

    An Extension to Hough Transform Based on Gradient Orientation

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    The Hough transform is one of the most common methods for line detection. In this paper we propose a novel extension of the regular Hough transform. The proposed extension combines the extension of the accumulator space and the local gradient orientation resulting in clutter reduction and yielding more prominent peaks, thus enabling better line identification. We demonstrate benefits in applications such as visual quality inspection and rectangle detection.Comment: Part of the Proceedings of the Croatian Computer Vision Workshop, CCVW 2015, Year

    Non-Visual Document Recognition for Blind Reading Assistant System

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    [[abstract]]As time goes on, a huge mass of progressive knowledge is developed and then the e-book is built for paper reduction and environmental protection. Therefore, many historical documents over the past don’t exist. Research on blind reading aid device is a popular topic gradually, but there are some drawbacks on these methods. For example, electronic documents of many old dated of historical documents don’t read because format should be limited to e-document. Users can’t read any specified region of the document as he wishes. A novel blind reading aid device is proposed without e-document and the user only need to point the document with his finger. This system is composed of third parts. First, we use rectangle detection method to catch the region for document under the Microsoft Kinect. Next, dilation method and projection profile methods are used in order to execrate text and constructed coordinate database. Finally, skin detection, BEA method and depth image of Microsoft Kinect can get the coordinates of user’s finger when user wishes to read the document, and then match with constructed coordinate database to get the character. Then system output is obtained via text to speech.[[notice]]補正完畢[[journaltype]]國外[[conferencetype]]國際[[conferencedate]]20130618~20130620[[ispeerreviewed]]Y[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Jeju Island, Republic of Korea[[countrycodes]]KO

    Desarrollo de una algoritmo para la localización automática de placas vehiculares peruanas usando técnicas de procesamiento de imágenes

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    La necesidad de identificar un vehículo está relacionada con el reconocimiento de las placas correspondientes; esto se hace necesario debido a que se podría tener un mejor control en casos de infracciones, así como robos o accidentes vehiculares. La seguridad ciudadana está ligada con estos factores, por lo que el desarrollo de un sistema automático de reconocimiento de placas vehiculares ayudaría a tener una ciudad más segura. Esta Tesis plantea como solución el desarrollo de un algoritmo para la localización automática de placas vehiculares basado en técnicas de procesamiento digital de imágenes, detecta placas hechas en el Perú, las cuales cuentan principalmente con caracteres oscuros en fondo de color uniforme. Se investiga algunos métodos existentes para la extracción de las regiones de interés en las imágenes, placas, describiendo las técnicas principales que resuelven la problemática, indicando la eficiencia de éxito y las dificultades de cada una de ellas. Consta de cuatro capítulos: en el primero, se detalla la importancia de desarrollar sistemas automáticos de identificación de placas en base al uso de aplicaciones prácticas y se indican las consideraciones generales que se toman en cuenta para delimitar el alcance del trabajo. En el segundo capítulo se describe el estado del arte lo cual consta de métodos que se utilizarán como referencia para la realización del trabajo propuesto. El tercer capítulo describe detalladamente el desarrollo del algoritmo planteado a partir de dos procesos principales: umbralización automática y extracción. El proceso de umbralización automática consiste en el cálculo del valor umbral para la obtención de la imagen binaria requerido para el siguiente proceso, se determinan los puntos de interés en base a las características de la existencia de caracteres en la imagen. El proceso de extracción logra extraer la región de la imagen que contiene la placa vehicular a partir de las propiedades geométricas de la misma. Por último, el capítulo cuatro expone los resultados obtenidos mediante el uso de una herramienta de software especializado en procesamiento de imágenes, se realizan comparaciones con algoritmos desarrollados inicialmente y se concluye el método más eficiente que cumple con el objetivo establecido.Tesi

    Object Tracking Implementation on Embedded Computing Platform

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    Embedded platforms are vital in various applications mainly Robotics and Mobile platforms. Image processing is usually done with full PC setup, which is hard to implement on mobile platforms and in other applications. This project aims to implement an image processing application on an embedded platform using structured C++ coding and OpenCV library

    Free-Shape Polygonal Object Localization

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    Polygonal objects are prevalent in man-made scenes. Early approaches to detecting them relied mainly on geometry while subsequent ones also incorporated appearance-based cues. It has recently been shown that this could be done fast by searching for cycles in graphs of line-fragments, provided that the cycle scoring function can be expressed as additive terms attached to individual fragments. In this paper, we propose an approach that eliminates this restriction. Given a weighted line-fragment graph, we use its cyclomatic number to partition the graph into managebly-sized sub-graphs that preserve nodes and edges with a high weight and are most likely to contain object contours. Object contours are then detected as maximally scoring elementary circuits enumerated in each sub-graph. Our approach can be used with any cycle scoring function and multiple candidates that share line fragments can be found. This is unlike in other approaches that rely on a greedy approach to finding candidates. We demonstrate that our approach significantly outperforms the state-of-the-art for the detection of building rooftops in aerial images and polygonal object categories from ImageNet

    Detection of incomplete enclosures of rectangular shape in remotely sensed images

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    We develop an approach for detection of ruins of livestock enclosures in alpine areas captured by high-resolution remotely sensed images. These structures are usually of approximately rectangular shape and appear in images as faint fragmented contours in complex background. We address this problem by introducing a new rectangularity feature that quantifies the degree of alignment of an optimal subset of extracted linear segments with a contour of rectangular shape. The rectangularity feature has high values not only for perfect enclosures, but also for broken ones with distorted angles, fragmented walls, or even a completely missing wall. However, it has zero value for spurious structures with less than three sides of a perceivable rectangle. Performance analysis using large imagery of an alpine environment is provided. We show how the detection performance can be improved by learning from only a few representative examples and a large number of negatives.Computer SciencesEuropean Prehistor

    Real-time landing place assessment in man-made environments

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    We propose a novel approach to the real-time landing site detection and assessment in unconstrained man-made environments using passive sensors. Because this task must be performed in a few seconds or less, existing methods are often limited to simple local intensity and edge variation cues. By contrast, we show how to efficiently take into account the potential sites' global shape, which is a critical cue in man-made scenes. Our method relies on a new segmentation algorithm and shape regularity measure to look for polygonal regions in video sequences. In this way, we enforce both temporal consistency and geometric regularity, resulting in very reliable and consistent detections. We demonstrate our approach for the detection of landable sites such as rural fields, building rooftops and runways from color and infrared monocular sequences significantly outperforming the state-of-the-art
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