Search results for "Computer Vision"
showing 10 items of 2353 documents
Objective improvement of the visual quality of ion microscope images
2013
The need to operate with low ion beam fluences implies the images obtained using ion microscope (IM) are often grainy and have poor visual quality compared to what can be obtained using e.g. confocal microscopy. This results from the Poissonian distribution of counts in pixels. Here we report work on some different approaches for objectively improving the visual quality of IM images. In this work we present (i) dramatic improvement in the visual image quality of off-axis and direct-scanning transmission ion microscopy (STIM) images by suppression of zero-pixels; (ii) denoising of PIXE images using wavelet filtering and (iii) use of the feature preserving characteristics of wavelet filtering…
Selective Change Driven Vision Sensor With Continuous-Time Logarithmic Photoreceptor and Winner-Take-All Circuit for Pixel Selection
2015
The objective of Selective Change Driven (SCD) Vision is to capture and process those scene pixels that have the greatest impact in the motion estimation task. The implemented SCD Vision sensor delivers the pixels ordered according to the illumination change undergone by each pixel, from the last time each pixel was read-out. This ordering strategy is especially interesting for motion detection algorithms, since it allows for a reduction in data bandwidth requirements without decreasing accuracy. The speed of the obtained pixel flow allows movement detection and tracking at a speed several orders of magnitude higher than conventional vision systems. To accomplish these objectives, the senso…
On the Advantages of Asynchronous Pixel Reading and Processing for High-Speed Motion Estimation
2008
Biological visual systems are becoming an interesting source for the improvement of artificial visual systems. A biologically inspired read-out and pixel processing strategy is presented. This read-out mechanism is based on Selective pixel Change-Driven (SCD) processing. Pixels are individually processed and read-out instead of the classical approach where the read-out and processing is based on complete frames. Changing pixels are read-out and processed at short time intervals. The simulated experiments show that the response delay using this strategy is several orders of magnitude lower than current cameras while still keeping the same, or even tighter, bandwidth requirements.
A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC
2009
This paper presents a comparative study on five feature selection heuristics applied to a retinal image database called DRIVE. Features are chosen from a feature vector (encoding local information, but as well information from structures and shapes available in the image) constructed for each pixel in the field of view (FOV) of the image. After selecting the most discriminatory features, an AdaBoost classifier is applied for training. The results of classifications are used to compare the effectiveness of the five feature selection methods.
Unsupervised recognition of retinal vascular junction points.
2014
Landmark points in retinal images can be used to create a graph representation to understand and to diagnose not only different pathologies of the eye, but also a variety of more general diseases. Aim of this paper is the description of a non-supervised methodology to distinguish between bifurcations and crossings of the retinal vessels, which can be used in differentiating between arteries and veins. A thinned representation of the binarized image, is used to identify pixels with three or more neighbors. Junction points are classified into bifurcations or crossovers according to their geometrical and topological properties. The proposed approach is successfully compared with the state-of-t…
Improving SIFT-based descriptors stability to rotations
2010
Image descriptors are widely adopted structures to match image features. SIFT-based descriptors are collections of gradient orientation histograms computed on different feature regions, commonly divided by using a regular Cartesian grid or a log-polar grid. In order to achieve rotation invariance, feature patches have to be generally rotated in the direction of the dominant gradient orientation. In this paper we present a modification of the GLOH descriptor, a SIFT-based descriptor based on a log-polar grid, which avoids to rotate the feature patch before computing the descriptor since predefined discrete orientations can be easily derived by shifting the descriptor vector. The proposed des…
Extract information of polarization imaging from local matching stereo
2010
Since polarization of light was used in the field of computer vision, the research of polarization vision is rapidly growing. Polarization vision has been shown to simplify some important image understanding tasks that can be more difficult to be performed with intensity vision. Furthermore, it has computational efficiency because it only needs grayscale images and can be easily applied by a simple optical setup. Nowadays, we can find various types of polarization cameras in the market. However, they are very expensive. In our work, we will study and develop a low price polarization camera setup with parallel acquisition using a stereo system. This system requires only two general cameras e…
Choosing local matching score method for stereo matching based-on polarization imaging
2010
Polarization imaging is a powerful tool to observe hidden information from an observed object. It has significant advantages, such as computational efficiency (it only needs gray scale images) and can be easily applied by adding a polarizer in front of a camera. Many researchers used polarization in various areas of computer vision, such as object recognition, segmentation and so on. However, there is very little research in stereo vision based on polarization. Stereo vision is a well known technique for obtaining depth information from pairs of stereo digital images. One of the main focuses of research in this area is to get accurate stereo correspondences. In our work, we will study and d…
Estimating intrinsic image from successive images by solving underdetermined and overdetermined systems of the dichromatic model
2020
International audience; Estimating an intrinsic image from a sequence of successive images taken from an object at different angles of illumination can be used in various applications such as objects recognition, color classification, and the like; because, in so doing, it can provide more visual information. Meanwhile, according to the well-known dichromatic model, each image can be considered a linear combination of three components, including intrinsic image, shading factor, and specularity. In this study, at first, two simple independent constrained and parallelized quadratic programming steps were used for computing values of the shading factor and the specularity of each successive of…
Adapted processing of catadioptric images using polarization imaging
2009
A non parametric method that defines a pixel neighborhood within catadioptric images is presented in this paper. It is based on an accurate modeling of the mirror shape by using polarization imaging. Unlike the most of current processing methods in the literature, this method is non-parametric and can deal with the deformation of catadioptric images. This paper demonstrates how an appropriate neighborhood can be derived from the polarization parameters by estimation of the degree of polarization and the angle of polarization which in return directly provide an adapted neighborhood of each pixel that can be used to perform image derivation, edge detection, interest point detection and namely…