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In this paper, we present an automated algorithm for detection of blood vessels in 2D-thermographic images for breast cancer screening. Vessel extraction from breast thermal images help in the classification of malignancy as cancer causes increased blood flow at warmer temperatures, additional vessel formation and tortuosity of vessels feeding the cancerous growth. The proposed algorithm uses three...
This paper investigates precise pupil center localization in low-resolution images. Being an essential preprocessing step in many applications such as gaze estimation, face alignment as well as human-computer interaction, robust, precise, and efficient methods are necessary. We present a method for accurate eye center localization operating with images from simple off-the-shelf hardware such as webcams...
3D-HEVC is the new coding standard dealing with both the texture and the associated depth video. In addition to some new coding tools designed for texture video with improved coding efficiency, some specified tools are devoted for depth video, such as depth modeling mode (DMM), segment-wise DC (SDC) mode and single depth intra mode. In this paper, we propose two techniques to speed up the encoding...
We developed an optical distortion correction technique for an eyeglasses-type wearable device using a multi-mirror array (MMA). This wearable device is small and light weight, but optics using MMA can cause optical distortions, such as geometric distortion and chromatic aberration of magnification, that depend on the user's pupil distance and degrade the visibility of displayed virtual images. We...
Multidimensional image data, i.e., images with three or more dimensions, are used in many areas of science. Multidimensional image proçessing is supported in Python and MATLAB. VisionGL is an open source library that provides a set of image processing functions and can help the programmer by automatically generating code. The objective of this work is to augment VisionGL by adding multidimensional...
The discrete Fourier transform is an important tool for processing digital images. Efficient algorithms for computing the Fourier transform are known as fast Fourier transforms (FFTs). One of the most common of these is the Cooley-Tukey radix-2 decimation algorithm that efficiently transforms one-dimensional data into its frequency domain representation. The orthogonality of rectangular sampling allows...
Content-aware image retargeting adjusts images to arbitrary sizes and preserves visually salient content. Previous algorithms formulate the problem in terms of either pixel level or mesh level structures, deforming salient objects inconsistently. To improve retargeting quality and reduce complexity, we introduced a patch-wise method to generate sparse image grids based on visual saliency and gradient...
Machine learning is a very promising way of solving some image processing tasks. However, existing approaches fails at integrating feature selection within the learning task. This paper introduces a new two stage learning algorithm called near infinitely linear combination (NILC) that performs at the same time variable selection and error minimization. Empirical evidence reported on different document...
Block truncation coding (BTC) has been considered as a highly efficient compression technique for decades, but the blocking artifact is its main issue. The halftoning-based BTC has significantly eased this issue, yet an apparent impulse noise artifact is accompanied. In this study, an improved BTC, termed adaptive dot-diffused BTC (ADBTC), is proposed to further improve the visual quality. Also, this...
In this paper, we propose a novel framework for nighttime image dehazing based on a nighttime haze model which accounts for varying light sources and their glow. First, glow effects are decomposed using relative smoothness. Atmospheric light is then estimated by combining global and local atmospheric lights using a local atmospheric selection map. The transmission is estimated by maximizing an objective...
Depth from defocus (DFD) technique calculates the blur amount in images considering that the depth and defocus blur are related to each other. Existing blur estimation methods generally compute the blur at edge locations and solve an optimization problem to propagate the blur from edges to all image pixels. Solving the pixel-based optimization problem is time-consuming and it is the performance bottleneck...
Traditional models for saliency analysis in satellite images cannot genuinely mimic the selection mechanism of human vision system. Furthermore, feature selection needs variant considering the complexity of data distribution of different satellite images thereby not being one-size-fits-all. Aiming at these problems, we propose a novel model based on sparse representation for saliency analysis with...
Saliency analysis is an effective method to extract interesting target regions from satellite images. However, when the satellite image contains salient background information, it is difficult to eliminate this information accurately only using single image saliency analysis. In this paper, a novel multiimage saliency analysis (MSA) model based on multiple multispectral images clustering saliency...
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply superresolution algorithms to realize an increased resolution. Those methods can be divided into approaches that rely on only a single low resolution image or on multiple low resolution video frames. While...
Cardiovascular diseases belong to the most widespread illnesses in the developed countries. Therefore, the regenerative medicine and tissue modeling applications are highly interested in studying the ability of endothelial cells, derived from human stem cells, to form vascular networks. Several characteristics can be measured on images of these networks and hence describe the quality of the endothelial...
This paper presents an efficient constant-time bilateral filter where constant-time means that computational complexity is independent of filter window size. Many state-of-the-art constant-time methods approximate the original bilateral filter by an appropriate combination of a series of convolutions. It is important for this framework to optimize the performance tradeoff between approximate accuracy...
This paper is concerned with the problem of anomaly detection on surfaces that show periodic decoration patterns as shown at car interior components for example. The decoration of the surface is allowed to show a smooth deformation that can vary from one sample to another. As a consequence, every sample is unique in its appearance. The task is to robustly distinguish between the regular decoration...
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