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Current Search:
All of 'Image' and 'processing' in all fields;
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Displaying Results 26 - 50 of 366 on page 2 of 15
Marked
Mark
Optimal Schemes for Motion Estimation on Colour Image Sequences
(1997)
KOKARAM, ANIL CHRISTOPHER
Optimal Schemes for Motion Estimation on Colour Image Sequences
(1997)
KOKARAM, ANIL CHRISTOPHER
Abstract:
This paper describes a method for incorporating the chrominance information when estimating the motion in a colour image sequence. It is based on a maximum likelihood formulation of the motion estimation problem which assumes homogeneous additive Gaussian noise in each colour component, with known inter-field correlation statistics. The formulation is applied to the complex-wavelet-domain matching algorithm of Magarey and Kingsbury (see Proc. IEEE Int. Conf. on Image Processing, p.969-72, 1996). We also define a noise-decorrelating colour space transform which provides a simple implementation of the ML formulation in the wavelet domain. Results for noisy synthesised colour sequences with known motion and noise statistics demonstrate the superiority of the exact ML formulation over straightforward, unweighted three-component estimation, most noticeably in high noise conditions
http://hdl.handle.net/2262/40127
Marked
Mark
Automated sorting of consumer image collections using face and peripheral region image classifiers
(2005)
Corcoran, Peter M.; Costache, Gabriel
Automated sorting of consumer image collections using face and peripheral region image classifiers
(2005)
Corcoran, Peter M.; Costache, Gabriel
Abstract:
An evaluation of techniques and recognition technologies for use in an automatic cataloging tool for consumer image collections is presented. A working implementation of an automatic cataloging tool and user search tools are described. Techniques for combining multiple classifiers derived from face and peripheral regions are discussed. Practical aspects of the requirements for a working in-camera solution are also discussed.
http://hdl.handle.net/10379/290
Marked
Mark
Content based image pose manipulation
(2009)
Begley, Seán
Content based image pose manipulation
(2009)
Begley, Seán
Abstract:
This thesis proposes the application of space-frequency transformations to the domain of pose estimation in images. This idea is explored using the Wavelet Transform with illustrative applications in pose estimation for face images, and images of planar scenes. The approach is based on examining the spatial frequency components in an image, to allow the inherent scene symmetry balance to be recovered. For face images with restricted pose variation (looking left or right), an algorithm is proposed to maximise this symmetry in order to transform the image into a fronto-parallel pose. This scheme is further employed to identify the optimal frontal facial pose from a video sequence to automate facial capture processes. These features are an important pre-requisite in facial recognition and expression classification systems. The under lying principles of this spatial-frequency approach are examined with respect to images with planar scenes. Using the Continuous Wavelet Transform, full pe...
http://doras.dcu.ie/2370/
Marked
Mark
Analyzing image-text relations for semantic media adaptation and personalization
(2007)
Hughes, Mark; Salway, Andrew; Jones, Gareth J.F.; O'Connor, Noel E.
Analyzing image-text relations for semantic media adaptation and personalization
(2007)
Hughes, Mark; Salway, Andrew; Jones, Gareth J.F.; O'Connor, Noel E.
Abstract:
Progress in semantic media adaptation and personalisation requires that we know more about how different media types, such as texts and images, work together in multimedia communication. To this end, we present our ongoing investigation into image-text relations. Our idea is that the ways in which the meanings of images and texts relate in multimodal documents, such as web pages, can be classified on the basis of low-level media features and that this classification should be an early processing step in systems targeting semantic multimedia analysis. In this paper we present the first empirical evidence that humans can predict something about the main theme of a text from an accompanying image, and that this prediction can be emulated by a machine via analysis of low- level image features. We close by discussing how these findings could impact on applications for news adaptation and personalisation, and how they may generalise to other kinds of multimodal documents and to applicatio...
http://doras.dcu.ie/439/
Marked
Mark
CTex - an adaptive unsupervised segmentation algorithm based on color-texture coherence
(2008)
Ilea, Dana E.; Whelan, Paul F.
CTex - an adaptive unsupervised segmentation algorithm based on color-texture coherence
(2008)
Ilea, Dana E.; Whelan, Paul F.
Abstract:
This paper presents the development of an unsupervised image segmentation framework (referred to as CTex) that is based on the adaptive inclusion of color and texture in the process of data partition. An important contribution of this work consists of a new formulation for the extraction of color features that evaluates the input image in a multispace color representation. To achieve this, we have used the opponent characteristics of the RGB and YIQ color spaces where the key component was the inclusion of the self organizing map (SOM) network in the computation of the dominant colors and estimation of the optimal number of clusters in the image. The texture features are computed using a multichannel texture decomposition scheme based on Gabor filtering. The major contribution of this work resides in the adaptive integration of the color and texture features in a compound mathematical descriptor with the aim of identifying the homogenous regions in the image. This integration is per...
http://doras.dcu.ie/4677/
Marked
Mark
Facial features and appearance-based classification for face detection in color images
(2004)
Cooray, Saman H.; O'Connor, Noel E.
Facial features and appearance-based classification for face detection in color images
(2004)
Cooray, Saman H.; O'Connor, Noel E.
Abstract:
A technique is presented for frontal face detection in color images based on facial feature extraction and appearance-based classification. Salient facial features are used to define a search space that is then used in a classification step in order to find the best position of the face in the image. Mouth feature points are identified using the redness property of image pixels whilst eye feature points are detected using a search strategy applied to a subset of regions in a fine region-based segmentation of the candidate face. Face class modeling based on a multivariate normal distribution and discriminating feature analysis is used as the face classification method. The utilization of facial features in this system avoids analyzing the image at every pixel location as well as at multiple scales when detecting faces of different sizes.
http://doras.dcu.ie/408/
Marked
Mark
Evaluation of 3D gradient filters for estimation of the surface orientation in CTC
(2006)
Chowdhury, Tarik A.; Ghita, Ovidiu; Whelan, Paul F.
Evaluation of 3D gradient filters for estimation of the surface orientation in CTC
(2006)
Chowdhury, Tarik A.; Ghita, Ovidiu; Whelan, Paul F.
Abstract:
The extraction of the gradient information from 3D surfaces plays an important role for many applications including 3D graphics and medical imaging. The extraction of the 3D gradient information is performed by filtering the input data with high pass filters that are typically implemented using 3×3×3 masks. Since these filters extract the gradient information in small neighborhood, the estimated gradient information will be very sensitive to image noise. The development of a 3D gradient operator that is robust to image noise is particularly important since the medical datasets are characterized by a relatively low signal to noise ratio. The aim of this paper is to detail the implementation of an optimized 3D gradient operator that is applied to sample the local curvature of the colon wall in CT data and its influence on the overall performance of our CAD-CTC method. The developed 3D gradient operator has been applied to extract the local curvature of the colon wall in a large number...
http://doras.dcu.ie/4645/
Marked
Mark
Automatic classification of shoeprints for use in forensic science based on the fourier transform
(2003)
REILLY, RICHARD
Automatic classification of shoeprints for use in forensic science based on the fourier transform
(2003)
REILLY, RICHARD
Abstract:
peer-reviewed
This study developed a system of automatic classification of shoeprint images into groups belonging to the same sole pattern. When presented with an image of a new shoeprint the system displays a ranked sequence of shoeprint images from the database. The shoeprint images are ranked from best match to worst match in terms of the pattern of the shoeprint. For this study a database of 503 shoeprint images belonging to 139 pattem groups was established with each group containing 2 or more examples. The pattern grouping was performed by a panel of human experts. This designed system is a fully automatic method and functions with minimum user intervention. Tests of the system have shown that the first shoeprint image displayed is a correct match 54% of the time and that a correct match appears within the first 5% of displayed shoeprints 75% of the time. The system has translational and rotational invariance so that the spatial positioning of the new shoeprint images does...
http://hdl.handle.net/2262/19580
Marked
Mark
Learning midlevel image features for natural scene and texture classification
(2007)
Le Borgne, Hervé; Guérin-Dugué, Anne; O'Connor, Noel E.
Learning midlevel image features for natural scene and texture classification
(2007)
Le Borgne, Hervé; Guérin-Dugué, Anne; O'Connor, Noel E.
Abstract:
This paper deals with coding of natural scenes in order to extract semantic information. We present a new scheme to project natural scenes onto a basis in which each dimension encodes statistically independent information. Basis extraction is performed by independent component analysis (ICA) applied to image patches culled from natural scenes. The study of the resulting coding units (coding filters) extracted from well-chosen categories of images shows that they adapt and respond selectively to discriminant features in natural scenes. Given this basis, we define global and local image signatures relying on the maximal activity of filters on the input image. Locally, the construction of the signature takes into account the spatial distribution of the maximal responses within the image. We propose a criterion to reduce the size of the space of representation for faster computation. The proposed approach is tested in the context of texture classification (111 classes), as well as natur...
http://doras.dcu.ie/252/
Marked
Mark
Capture, processing, and display of real-world 3D objects using digital holography
(2010)
Naughton, Thomas J.; Falldortt, Claas; Onural, Levent; Ferraro, Pietro
Capture, processing, and display of real-world 3D objects using digital holography
(2010)
Naughton, Thomas J.; Falldortt, Claas; Onural, Levent; Ferraro, Pietro
Abstract:
"Digital holography for 3D and 4D real-world objects' capture, processing, and display" (acronym "Real 3D") is a research project funded under the Information and Communication Technologies theme of the European Commission's Seventh Framework Programme, and brings together nine participants from academia and industry (see www.digitalholography.eu).This three-year project marks the beginning a long-term effort to facilitate the entry of a new technology (digital holography) into the three-dimensional capture and display markets. Its progress at the end of year 2 is summarised.
http://eprints.nuim.ie/2328/
Marked
Mark
Diversity in image retrieval: DCU at ImageCLEFPhoto 2008
(2008)
O'Hare, Neil; Wilkins, Peter; Gurrin, Cathal; Newman, Eamonn; Jones, Gareth J.F.; ...
Diversity in image retrieval: DCU at ImageCLEFPhoto 2008
(2008)
O'Hare, Neil; Wilkins, Peter; Gurrin, Cathal; Newman, Eamonn; Jones, Gareth J.F.; Smeaton, Alan F.
Abstract:
DCU participated in the ImageCLEF 2008 photo retrieval task, submitting runs for both the English and Random language annotation conditions. Our approaches used text-based and image-based retrieval approaches to give baseline retrieval runs, with the highest-ranked images from these baseline runs clustered using K-Means clustering of the text annotations. Finally, each cluster was represented by its most relevant image and these images were ranked for the nal submission. For random annotation language runs, we used TextCat1 to identify German annotation documents, which were then translated into English using Systran Version:3.0 Machine Translator. We also compared results from these translated runs with untranslated runs. Our results showed that, as expected, runs that combine image and text outperform text alone and image alone. Our baseline image+text runs (i.e. without clustering) give our best MAP score, and these runs also outperformed the mean and median ImageCLEFPhoto submis...
http://doras.dcu.ie/651/
Marked
Mark
Image segmentation, evaluation, and applications
(2010)
McGuinness, Kevin
Image segmentation, evaluation, and applications
(2010)
McGuinness, Kevin
Abstract:
This thesis aims to advance research in image segmentation by developing robust techniques for evaluating image segmentation algorithms. The key contributions of this work are as follows. First, we investigate the characteristics of existing measures for supervised evaluation of automatic image segmentation algorithms. We show which of these measures is most effective at distinguishing perceptually accurate image segmentation from inaccurate segmentation. We then apply these measures to evaluating four state-of-the-art automatic image segmentation algorithms, and establish which best emulates human perceptual grouping. Second, we develop a complete framework for evaluating interactive segmentation algorithms by means of user experiments. Our system comprises evaluation measures, ground truth data, and implementation software. We validate our proposed measures by showing their correlation with perceived accuracy. We then use our framework to evaluate four popular interactive segmenta...
http://doras.dcu.ie/14998/
Marked
Mark
Multi-resolution texture classification based on local image orientation
(2008)
Ghita, Ovidiu; Whelan, Paul F.; Ilea, Dana E.
Multi-resolution texture classification based on local image orientation
(2008)
Ghita, Ovidiu; Whelan, Paul F.; Ilea, Dana E.
Abstract:
The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image orientation is extracted using the partial derivatives of the Gaussian function. Since the texture descriptors are dependent on the observation scale, in this study the main emphasis is placed on the implementation of multi-resolution texture analysis schemes. The experimental results were obtained when the analysed texture descriptors were applied to standard texture databases.
http://doras.dcu.ie/4692/
Marked
Mark
A multistage hierarchical algorithm for hand shape recognition
(2009)
Farouk , Moahmed; Sutherland, Alistair; Shoukry, Amin A.
A multistage hierarchical algorithm for hand shape recognition
(2009)
Farouk , Moahmed; Sutherland, Alistair; Shoukry, Amin A.
Abstract:
This paper represents a multistage hierarchical algorithm for hand shape recognition using principal component analysis (PCA) as a dimensionality reduction and a feature extraction method. The paper discusses the effect of image blurring to build data manifolds using PCA and the different ways to construct these manifolds. In_order to classify the hand shape of an incoming sign object and to be invariant to linear transformations like translation and rotation, a multistage hierarchical classifier structure is used. Computer generated images for different Irish Sign Language shapes are used in testing. Experimental results are given to show the accuracy and performance of the proposed algorithm.
http://doras.dcu.ie/14952/
Marked
Mark
Fast Image Interpolation for Motion Estimation using Graphics Hardware,
(2004)
KOKARAM, ANIL CHRISTOPHER
Fast Image Interpolation for Motion Estimation using Graphics Hardware,
(2004)
KOKARAM, ANIL CHRISTOPHER
Abstract:
Motion estimation and compensation is the key to high quality video coding. Block matching motion estimation is used in most video codecs, including MPEG-2, MPEG-4, H.263 and H.26L. Motion estimation is also a key component in the digital restoration of archived video and for post-production and special effects in the movie industry. Sub-pixel accurate motion vectors can improve the quality of the vector field and lead to more efficient video coding. However sub-pixel accuracy requires interpolation of the image data. Image interpolation is a key requirement of many image processing algorithms. Often interpolation can be a bottleneck in these applications, especially in motion estimation due to the large number pixels involved. In this paper we propose using commodity computer graphics hardware for fast image interpolation. We use the full search block matching algorithm to illustrate the problems and limitations of using graphics hardware in this way.
http://hdl.handle.net/2262/37026
Marked
Mark
Feature-Assisted Sparse to Dense Motion Estimation using Geodesic Distances.
(2009)
RING, DANIEL; PITIE, FRANCOIS
Feature-Assisted Sparse to Dense Motion Estimation using Geodesic Distances.
(2009)
RING, DANIEL; PITIE, FRANCOIS
Abstract:
Large motion displacements in image sequences are still a problem for most motion estimation techniques. Progress in feature matching allows to establish robust correspondences between images for a sparse set of points. Recent works have attempted to use this sparse information to guide the dense motion field estimation. We propose to achieve this in an extended motion estimation framework, which integrates information about the geodesic distance to the sparse features. Results show that by considering a handful of these feature matches, the geodesic distance is able to propagate the information efficiently.
http://hdl.handle.net/2262/39299
Marked
Mark
Optimising the number of channels in EEG-augmented image search
(2011)
Healy, Graham; Smeaton, Alan
Optimising the number of channels in EEG-augmented image search
(2011)
Healy, Graham; Smeaton, Alan
Abstract:
Recent proof-of-concept research has appeared showing the applicability of Brain Computer Interface (BCI) technology in combination with the human visual system, to classify images. The basic premise here is that images that arouse a participant’s attention generate a detectable response in their brainwaves, measurable using an electroencephalograph (EEG). When a participant is given a target class of images to search for, each image belonging to that target class presented within a stream of images should elicit a distinctly detectable neural response. Previous work in this domain has primarily focused on validating the technique on proof of concept image sets that demonstrate desired properties and on examining the capabilities of the technique at various image presentation speeds. In this paper we expand on this by examining the capability of the technique when using a reduced number of channels in the EEG, and its impact on the detection accuracy.
http://doras.dcu.ie/16387/
Marked
Mark
Image processing for smart browsing of ocean colour data products and subsequent incorporation into a multi-modal sensing framework
(2010)
O'Connor, Edel; Hayes, Jer; O'Conaire, Ciarán; Smeaton, Alan F.; O'Conno...
Image processing for smart browsing of ocean colour data products and subsequent incorporation into a multi-modal sensing framework
(2010)
O'Connor, Edel; Hayes, Jer; O'Conaire, Ciarán; Smeaton, Alan F.; O'Connor, Noel E.; Diamond, Dermot
Abstract:
Ocean colour is defined as the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments and coloured dissolved organic material and so water colour can provide valuable information on coastal ecosystems. The ‘Ocean Colour project’ collects data from various satellites (e.g. MERIS, MODIS) and makes this data available online. One method of searching the Ocean Colour project data is to visually browse level 1 and level 2 data. Users can search via location (regions), time and data type. They are presented with images which cover chlorophyll, quasi-true colour and sea surface temperature (11 μ) and links to the source data. However it is often preferable for users to search such a complex and large dataset by event and analyse the distribution of colour in an image before examination of the source data. This will allow users to browse and search ocean colour data more efficiently and to include this information more seamlessly into a framework that inc...
http://doras.dcu.ie/16116/
Marked
Mark
Stopping region-based image segmentation at meaningful partitions
(2007)
Adamek, Tomasz; O'Connor, Noel E.
Stopping region-based image segmentation at meaningful partitions
(2007)
Adamek, Tomasz; O'Connor, Noel E.
Abstract:
This paper proposes a new stopping criterion for automatic image segmentation based on region merging. The criterion is dependent on image content itself and when combined with the recently proposed approaches to syntactic segmentation can produce results aligned with the most salient semantic regions/objects present in the scene across heterogeneous image collections. The method identifies a single iteration from the merging process as the stopping point, based on the evolution of an accumulated merging cost during the complete merging process. The approach is compared to three commonly used stopping criteria: (i) required number of regions, (ii) value of the least link cost, and (iii) Peak Signal to Noise Ratio (PSNR). For comparison, the stopping criterion is also evaluated for a segmentation approach that does not use syntactic extensions. All experiments use a manually generated segmentation ground truth and spatial accuracy measures. Results show that the proposed stopping cri...
http://doras.dcu.ie/451/
Marked
Mark
Performance characterization of clustering algorithms for colour image segmentation
(2006)
Ilea, Dana E.; Whelan, Paul F.; Ghita, Ovidiu
Performance characterization of clustering algorithms for colour image segmentation
(2006)
Ilea, Dana E.; Whelan, Paul F.; Ghita, Ovidiu
Abstract:
This paper details the implementation of three traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation process. The aim of this paper is to evaluate the performance of the analysed colour clustering techniques for the extraction of optimal features from colour spaces and investigate which method returns the most consistent results when applied on a large suite of mosaic images.
http://doras.dcu.ie/4665/
Marked
Mark
Image metadata estimation using independent component analysis and regression
(2006)
Blighe, Michael; Le Borgne, Hervé; O'Connor, Noel E.
Image metadata estimation using independent component analysis and regression
(2006)
Blighe, Michael; Le Borgne, Hervé; O'Connor, Noel E.
Abstract:
In this paper, we describe an approach to camera metadata estimation using regression based on Independent Component Analysis (ICA). Semantic scene classification of images using camera metadata related to capture conditions has had some success in the past. However, different makes and models of camera capture different types of metadata and this severely hampers the application of this kind of approach in real systems that consist of photos captured by many different users. We propose to address this issue by using regression to predict the missing metadata from observed data, thereby providing more complete (and hence more useful) metadata for the entire image corpus. The proposed approach uses an ICA based approach to regression.
http://doras.dcu.ie/416/
Marked
Mark
SenseCam image localisation using hierarchical SURF trees
(2009)
Ó Conaire, Ciarán; Blighe, Michael; O'Connor, Noel E.
SenseCam image localisation using hierarchical SURF trees
(2009)
Ó Conaire, Ciarán; Blighe, Michael; O'Connor, Noel E.
Abstract:
The SenseCam is a wearable camera that automatically takes photos of the wearer's activities, generating thousands of images per day. Automatically organising these images for efficient search and retrieval is a challenging task, but can be simplified by providing semantic information with each photo, such as the wearer's location during capture time. We propose a method for automatically determining the wearer's location using an annotated image database, described using SURF interest point descriptors. We show that SURF out-performs SIFT in matching SenseCam images and that matching can be done efficiently using hierarchical trees of SURF descriptors. Additionally, by re-ranking the top images using bi-directional SURF matches, location matching performance is improved further.
http://doras.dcu.ie/2248/
Marked
Mark
An investigation into the use of jpeg image compression for digital photogrammetry: does the compression of images affect measurement accuracy
(1994)
Carswell, James D.
An investigation into the use of jpeg image compression for digital photogrammetry: does the compression of images affect measurement accuracy
(1994)
Carswell, James D.
Abstract:
Combining techniques used in image processing, digital photogrammetry has been proven to significantly increase productivity over analytical methods. In certain areas, digital photogrammetry has shown itself to be far superior to conventional methods of data collection. Softcopy (digital) photogrammetry raster files take up large amounts of storage space. Larger pixel sizes may help to reduce file size, but it has been shown in studies that larger pixel sizes may lead to less accurate results. What is the user to do? The importance of file compression should not be underestimated. File sizes affect almost every step of the digital photogrammetric workflow. Without some type of significant file compression, the entire process becomes complicated with excessive data file management. Depending on the specific workflow, file sizes are also critical in desktop environments where data storage may be small (e.g. heads-up digitising on digital orthophotos in a PC environment). ...
http://arrow.dit.ie/dmcart/27
Marked
Mark
Creation of virtual worlds from 3D models retrieved from content aware networks based on sketch and image queries
(2011)
Semertzidis, Theodoros; McGuinness, Kevin; Daras , Petros ; Makris, Lambros; O'Con...
Creation of virtual worlds from 3D models retrieved from content aware networks based on sketch and image queries
(2011)
Semertzidis, Theodoros; McGuinness, Kevin; Daras , Petros ; Makris, Lambros; O'Connor, Noel E.; Strintzis, Michael G.
Abstract:
The recent emergence of user generated content requires new content creation tools that will be both easy to learn and easy to use. These new tools should enable the user to construct new high-quality content with minimum effort; it is essential to allow existing multimedia content to be reused as building blocks when creating new content. In this work we present a new tool for automatically constructing virtual worlds with minimum user intervention. Users can create these worlds by drawing a simple sketch, or by using interactively segmented 2D objects from larger images. The system receives as a query the sketch or the segmented image, and uses it to find similar 3D models that are stored in a Content Centric Network. The user selects a suitable model from the retrieved models, and the system uses it to automatically construct a virtual 3D world.
http://doras.dcu.ie/16308/
Marked
Mark
Ridgelet-based signature for natural image classification
(2005)
Le Borgne, Hervé; O'Connor, Noel E.
Ridgelet-based signature for natural image classification
(2005)
Le Borgne, Hervé; O'Connor, Noel E.
Abstract:
This paper presents an approach to grouping natural scenes into (semantically) meaningful categories. The proposed approach exploits the statistics of natural scenes to define relevant image categories. A ridgelet-based signature is used to represent images. This signature is used by a support vector classifier that is well designed to support high dimensional features, resulting in an effective recognition system. As an illustration of the potential of the approach several experiments of binary classifications (e.g. city/landscape or indoor/outdoor) are conducted on databases of natural scenes.
http://doras.dcu.ie/317/
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