Object Extraction Research Papers - Academia.edu (original) (raw)

Three dimensional object extraction and recognition (OER) from LIDAR data has been an area of major interest in photogrammetry for quite a long time. However, most of the existing methods for automatic object extraction and recognition from LIDAR data are just based on the range information and employ parametric methods and object’s vagueness behaviour is basically neglected. Thus, these methods do not take into account the extraction and recognition complexities and may fail to reach a satisfied reliability level in complex situations. In this paper a novel approach based on the following strategies is formulated and implemented: (a) for a more comprehensive definition of the objects, information fusion concept is utilized, i.e., object’s descriptive components such as 3D structural and textural (ST) information are automatically extracted from first/last rang and intensity information of LIDAR data and simultaneously fed into the evaluation process, (b) for a more realistic expres...

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- Fuzzy Logic, Recognition, LiDAR, Region growing
- by alain pierret
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- Soil Science, Image Analysis, Mathematical Morphology, Biological Sciences

This paper presents a review of the current liter- ature on rough set and near set-based approaches to solving various problems in medical imaging such as medical image segmentation, object extraction and image classification. Rough set frameworks hybridized with other computational intelligence technologies that include neural networks, particle swarm op- timization, support vector machines and fuzzy sets are also presented.

— This project deals with the exposition of how robotics can be applied to various fields of agriculture. One of the most important occupations in a developing country like India is agriculture. It is very important to improve the efficiency and productivity of agriculture by replacing laborer with intelligent machines like robots using latest technologies. The project proposes a new strategy to replace humans in various agricultural operations like detection of presence of pests, spraying of pesticides, spraying of fertilizers, etc. there by providing safety to the farmers and precision agriculture. The developed system involves designing a prototype which uses simple cost effective equipment's like microprocessors, wireless camera, various motors and terminal equipment's which is an aid to the farmers in various crop field activities.

- by IJSRD - International Journal for Scientific Research and Development and +1
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- Electrical Engineering, Image Analysis, Robots, Object Extraction
- by Dr. Mahdi Fahmideh
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- Software Engineering, Pattern Recognition, Method Engineering, Pattern Mining

Nowadays, remotely sensed images are used for various purposes in different applications. One of them is the cadastral application using high resolution satellite imagery. In this context, a comparison of extraction results from these images and existing vector data is the most important issue. The goal here is to show the advantages and disadvantages of the QuickBird and IKONOS imagery for making cadastral maps. In this study, high resolution IKONOS and QuickBird images of rural and urban test areas in Zonguldak and Bartın have been chosen. Firstly, pan-sharpened IKONOS and QuickBird images have been produced by fusion of high resolution PAN and MS images using PCI Geomatica v9.1 software package. The parcel, building and road network objects from these datasets have been extracted automatically by initially dividing it into segments and then being classified by using the spectral, spatial and contextual information in eCognition v4.0.6 software package. On the other hand, these ob...

- by Merve Marangoz
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- Image Processing, Remote Sensing, Cadastral Systems, Remote sensing and GIS

The recording and 3D modeling of large Cultural Heritage sites is currently receiving much attention. This has two main reasons. On the one hand UNESCO pays more attention to large cultural and natural sites and on the other hand we have a wide array of new technologies available which greatly support the efficient generation, administration and analysis of such models.

- by Armin Gruen
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- Cultural Heritage, Peru, New Technology, Data acquisition

We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacement of the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvements finally increase the recognition rate of gaits.

- by DaeHee Kim
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- Object Tracking, Active Shape Model, Object Extraction, Gait Recognition

A simple but very efficient technique of 3D object reconstruction and recognition is presented here. An optical and computer vision based measurement system is used to acquire the object's data. The recognition algorithm is a distance calculator. It is used to compute the proximity of the object's shape under test and a reference object's geometry shape. Here, as an application example, we presents a human face recognition case. The effectiveness of the algorithm is demonstrated here in two tests in which the same person is compared with himself within different facial expressions and with others persons with different faces expressions too. The results are presented in a comparative chart.

- by Jorge Barreto
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- Computer Vision, Face Recognition, Facial expression, Object Extraction
- by Wolfgang Reinhardt and +1
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- Feature Extraction, Satellite Imagery, Object Extraction, Level
- by Kirrie Ballard
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- Treatment Outcome, Humans, Female, Male
- by Rajasvaran Logeswaran and +1
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- Information Systems, Algorithms, Magnetic Resonance Imaging, Humans

Nowadays three dimension (3D) architectural visualisation has become a powerful tool in the
conceptualisation, design and presentation of architectural products in the construction industry, providing
realistic interaction and walkthrough on engineering products. Traditional ways of implementing 3D
models involves the use of specialised 3D authoring tools along with skilled 3D designers with blueprints of
the model and this is a slow and laborious process. The aim of this paper is to automate this process by
simply analyzing the blueprint document and generating the 3D scene automatically. For this purpose we
have devised a 3-Phase recognition approach to pseudo 3D building generation from 2D floor plan and
developed a software accordingly.
Our 3-phased 3D building system has been implemented using C, C++ and OpenCV library [24] for the
Image Processing module; The Save Module generated an XML file for storing the processed floor plan
objects attributes; while the Irrlitch [14] game engine was used to implement the Interactive 3D module.
Though still at its infancy, our proposed system gave commendable results. We tested our system on 6 floor
plans with complexities ranging from low to high and the results seems to be very promising with an
average processing time of around 3s and a 3D generation in 4s. In addition the system provides an
interactive walk-though and allows users to modify components.

- by Daniel Cohenor
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- Information Systems, Computer Vision, Computer Animation, Segmentation
- by aboul ella hassanien
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- Engineering, Algorithms, Artificial Intelligence, Image Processing
- by Mamta Juneja
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- Information Security, Object Extraction, Normalized Cut, Data Transmission
- by Janer So Non
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- Object Classification, Object Extraction, Automatic Classification, Proof of Concept
- by aditi roy
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- Engineering, Algorithms, Artificial Intelligence, Content Management
- by Patrick Dickinson and +1
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- Cognitive Science, Image Recognition (Computer Vision), Image segmentation, FPGA implementation
- by Abdi Jemal
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- Image Processing, Remote Sensing, Cadastre, Object Extraction

Forest fire is an important issue that damages thousands of hectares of forest and all creatures inside it. In this study we have developed an early fire detection system running on low-cost, lightweight Raspberry Pi module integrated with an infrared camera. The infrared camera acquires the live video of the fields, then if a fire occurs, our software detects the fire by taking both motion and color characteristics of a flames into account. In our study, there exist two phases: first, motion detection phase is applied to the view, if a motion is detected in the view, then, color detection phase is applied to determine the flames. Obtained results indicates that our fire detection system can detect a forest fire clearly and smoothly without requiring any external equipment and manual intervention

- by Emrullah YILDIRIM
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- Computer Vision, Fire Detecting System, Object Extraction, Image Proccessing
- by Luigi Fregonese
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- Image Processing, Photogrammetry, LiDAR, Aerial Photogrammetry

In literature, several methods are available to combine both low spatial multispectral and low spectral panchromatic resolution images to obtain a high resolution multispectral image. One of the most common problems encountered in these methods is spectral distortions introduced during the merging process. At the same time, the spectral quality of the image is the most important factor affecting the accuracy of the results in many applications such as object recognition, object extraction, image analysis. In this study, the most commonly used methods including GIHS, GIHSF, PCA and Wavelet are analyzed using image quality metrics such as SSIM, ERGAS and SAM. At the same time, Wavelet is the best method for obtaining the fused image having the least spectral distortions according to obtained results. At the same time, image quality of GIHS, GIHSF and PCA methods are close to each other, but spatial qualities of the fused image using the wavelet method are less than others.

- by Altan Mesut
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- Geophysics, Algorithms, Image Processing, Remote Sensing
- by Roberto Tagliaferri and +2
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- Data Mining, Virtual Observatory, Soft Computing, Neural Networks
- by Tong-Yee Lee Lee
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- Information Systems, Computer Vision, Computer Animation, Collision detection
- by Rihana Mason
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- Psychology, Cognitive Science, Semantics, Cognition
- by Sara Saeedi
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- Honey bee, Data Collection, Data Clustering, Object Extraction
- by Muhammad Attique
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- Cognitive Science, Computer Vision, Biomedical Engineering, Image Processing

Abstract—Visual attention detection is an important technique in many computer vision applications. In this paper, we propose an algorithm to extract a salient object from an image using bottom-up and top-down computations. In bottomup computation, segment-based color contrast and attention values are employed to compose a bottom-up saliency map. In top-down computation, in-focus areas of the image are extracted to derive attention values using wavelet transforms for constructing a segment-based top-down saliency map. Attention values from both maps are combined by linear combination. The foreground/background-based salient object extraction is applied to form an output object. Experiments on 1,200 color images show that the proposed algorithm yields high level of satisfaction. I.

- by Wittawin Susutti
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- Computer Science, Computer Vision, Visual attention, Image segmentation
- by Pilar Merchán
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- Signal Processing, Pattern Recognition, Image Analysis, Localization

Video surveillance always had a negative connotation, among others because of the loss of privacy and because it may not automatically increase public safety. If it was able to detect atypical (i.e. dangerous) situations in real time, autonomously and anonymously, this could change. A prerequisite for this is an automatic detection of possibly dangerous situations from video data. From the derived trajectories we then want to determine dangerous situations by detecting atypical trajectories. However, it is better to develop such a system without people being threatened or even harmed, plus with having them know that there is such a tracking system installed. In the artistic project leave a trace the tracked people become actor and thus part of the installation. Visualization in real-time allows interaction by these actors, which in turn creates many atypical interaction situations on which we could develop our situation detection.

- by Daniel Casasanto
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- Psychology, Cognitive Science, Music, Perception
- by Georgy Gimel'farb
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- Information Systems, Algorithms, Artificial Intelligence, Remote Sensing
- by Nikhil Pal
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- Information Theory, Pattern Recognition, Entropy, Object Extraction
- by Uwe Stilla
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- Remote Sensing, Archives, Orthophoto & DEM Generation, Satellite Data
- by Yu-Yin Hsu
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- Object Extraction
- by Farhad Samadzadegan and +1
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- Honey bee, Data Collection, Data Clustering, Object Extraction
- by Edward Gibson
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- Cognition, Speech perception, Experience Design, Linguistics
- by Mufit Cetin
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- Geophysics, Algorithms, Image Processing, Remote Sensing

Image segmentation and object extraction plays an important role in image analysis and computer vision. In this paper, we propose a novel technique for color image segmentation called 'adaptive neuro-fuzzy color image seg- mentation (ANFCIS)'.The proposed system consists of multilayer perceptron (MLP)-like network which performs color image segmentation using multilevel thresholding. Threshold values for detecting clusters and their labels are

- by Ganeshchandra Shinde
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- Computer Vision, A Priori Knowledge, Image Analysis, Neural Network

An efficient hierarchical visual representation is proposed for progressive content-based image indexing and retrieval. More specifically, the image content is decomposed at different description levels, each of which represents the image at a different content scale. This is implemented by partitioning the image into objects structured in a hierarchical way. The lowest description level is obtained by applying a color segmentation algorithm to the image. On the other hand, the highest level is achieved by a semantic segmentation implemented in a semi-automatic framework. The spatial relationship of the object extracted, at a given description level, is described by a graph structure scheme. In particular, for each object (segment) a graph node is constructed and includes several features of that object. The graph links indicate the spatial relationship of the object with its neighbors. Following the hierarchical object decomposition, a tree-structure is created, providing efficient representation of the visual content.

- by Stefanos Kollias
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- Computer Science, Information Retrieval, Data Mining, Image segmentation

- by Muhammad Dawood
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- Image Processing, Pattern Recognition, Recognition, Construction Industry

Using Individual Human Knowledge Model (IHK model), which is designed focusing on the difference of each human's knowledge, we analyzed the results and design process of an application of Method of Object Extraction for Architecture (OEA method) to real house building project. OEA method is a new method aiming to realize an architecture free from the existing

- by Yukari Nagai
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- Design process, Object Extraction