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Nowadays, content-based image-retrieval techniques constitute powerful tools for archiving and mining of large remote sensing image databases. High spatial resolution images are complex and differ widely in their content, even in the same category. All images are more or less textured and structured. If the image to recognize is somewhat or very structured, a shape feature will be somewhat or very...
In this paper, we present a method to detect changes in high resolution remote sensing images based on superparsing proposed by Tighe et al. By comparing with several superpixel segmentation methods, we choose the SLIC (Simple Linear Iterative Clustering) method which can keep image boundary, produce consistent superpixels with similar size and shape, and also calculates fast. After superpixel segmentation,...
In the previous report, we have proposed a novel disease classification method based on eyeball shape parameters related to high myopia disease prognosis, by measuring 3-dimensional eyeball features without invasion using MRI. In order to apply the proposed method, we had to create volume-rendered images of each eyeball after 3D-MRI T2-weighted scanning of a head. In other words, we could not apply...
In this paper, we present a new and freely available dataset comprising 80 pages of an historical handwritten Arabic document in conjunction with a detailed ground truth for the development and evaluation of segmentation-free word spotting approaches. Besides information on the underlying manuscript and technical details, we introduce a comprehensive list of tags that each word is labeled with. These...
Object based image analysis on very high resolution (VHR) remote sensing imagery often ignores the heterogeneous constitution of feature spaces. In this paper, a supervised multiview feature selection (SMFS) method is proposed. In this method, features are decomposed into multiple disjoint and meaningful feature subsets by employing affinity propagation, where each feature subset represents a view,...
Although eye detection has been studied for a long time in academic and industrial communities, it is still a changeling problem if facial images are with varying head poses, facial expressions, illuminations and resolution changes etc., which tend to happen in uncontrolled conditions. In this work, we propose to learn deep features that could capture the appearance variations of eyes for eye detection...
Criminal and victim identification is always vital in forensic investigation. Many biometric traits, such as DNA, fingerprint, face and palm print, have been regularly used by law enforcement agencies. However, they are not applicable to legal cases where only non-facial body sites of criminals or victims in evidence images are available for identification. These cases include but are not limited...
This paper considers the problem of script and nature identification at word level. We introduce Pyramid Histogram of Oriented Gradients (PHOG) features which have been employed successfully for discriminating between handwritten and machine-printed Arabic and Latin scripts. Most of the image features, used in previous identification system, are not effective to capture differences between these scripts...
Efficient and effective image enlargement without distortion attracts numerous interests these days. This paper presents an image enlargement system for images with repetitive components. Based on repetitive components and seam filling, our system achieves distortion-free visual effect. Our system captures and extracts the repetitive components by MSERs. After which, we got the repetitive component...
For the new generation of spaceborne SAR sensors a resolution even better than one meter in the spotlight acquisition mode can be obtained. However, due to the involved electromagnetic mechanisms dictating SAR image formation, direct interpretation of very high-resolution (VHR) SAR images is not straightforward. In this paper, we propose the use of the power spectral density (PSD) for the analysis...
Pixel-scale fine details are often lost during image processing tasks such as image reduction and filtering. Block or region based algorithms typically rely on averaging functions to implement the required operation and traditional function choices struggle to preserve small, spatially cohesive clusters of pixels which may be corrupted by noise. This article proposes the construction of fuzzy measures...
In this paper, we propose a new image labeling algorithm for object analysis of the binary images. With one-scan process, the foreground (object) pixel is assigned a provisional label, and label equivalences between provisional labels are merged later. Our approach merges the region of the labeling of the foreground image during the one-scan labeling process. Compared with the existing conventional...
In this article, we focus on the comparison of the passive techniques of multi-view 3D reconstruction, namely the following techniques : Passive Stereo vision, Shape from Silhouette and Space Carving. Available data in the Passive techniques are no more than one or many images taken from different point of views (using one or several cameras). These images will be used in order to render the three-dimensional...
Superresolution from plenoptic cameras or camera arrays is usually treated similarly to superresolution from video streams. However, the transformation between the low-resolution views can be determined precisely from camera geometry and parallax. Furthermore, as each low-resolution image originates from a unique physical camera, its sampling properties can also be unique. We exploit this option with...
Endowing mobile manipulation robots with skills to use objects and tools often involves the programming or training on specific object instances. To apply this knowledge to novel instances from the same class of objects, a robot requires generalization capabilities for control as well as perception. In this paper, we propose an efficient approach to deformable registration of RGB-D images that enables...
This paper presents a novel approach for automatic detection of microaneurysms and haemorrhages in fundus images. First, it begins with a preprocessing stage for shade correction, contrast enhancement and denoising. Second, all regional minima with sufficient contrast are extracted and considered as candidates. Third, in an image flooding scheme, a new set of dynamic shape features is computed as...
Myeloarchitecture of cerebral cortex has crucial implication on the function of cortical columnar modules. Based on the recent development of high-field magnetic resonance imaging (MRI), it was demonstrated that it is possible to individually reconstruct such intracortical microstructures. However, there is a scarcity of publicly available frameworks to perform group-wise statistical inferences on...
In this paper, we propose a new book digitization system that can obtain high-resolution document images while flipping the pages automatically. The distinctive feature of our system is the adaptive capturing that has a crucial role in achieving high speed and high resolution. This adaptive capturing requires observing the state of the flipped pages at high speed and with high accuracy. In order to...
Depth map super resolution from multi-view depth or color images has long been explored. Multi-view stereo methods produce fine details at texture areas, and depth recordings would compensate when stereo doesn't work, e.g. at non-texture regions. However, resolution of depth maps from depth sensors are rather low. Our objective is to produce a high-res depth map by fusing different sensors from multiple...
With fast intensification of existing multimedia documents and mounting demand for information indexing and retrieval, much effort has been done on extracting the text from images and videos. Extracting the text from video is demanding due to complex background, varying font size, different style, high blurring, lower resolution, different position, viewing angle and so on. In this paper, implementation...
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