Search results for "Pattern Recognition"
showing 10 items of 2301 documents
Statistical Shape and Probability Prior Model for Automatic Prostate Segmentation
2011
International audience; Accurate prostate segmentation in Trans Rectal Ultra Sound (TRUS) images is an important step in different clinical applications. However, the development of computer aided automatic prostate segmentation in TRUS images is a challenging task due to low contrast, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow, and speckle. Significant variations in prostate shape, size and contrast between the datasets pose further challenges to achieve an accurate segmentation. In this paper we propose to use graph cuts in a Bayesian framework for automatic initialization and propagate multiple mean parametric models derived from princi…
Convolutional Neural Networks for Multispectral Image Cloud Masking
2020
Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.
Detection performance of normal cats and those lacking areas 17 and 18: a behavioral approach to analyse pattern recognition deficits.
1986
The ability of cats to discriminate between two geometrical outline patterns in the presence of superimposed Gaussian visual noise was tested before and after bilateral removal of cortical area 17 and parts of area 18. The detection probability PD was measured as a function of the signal-to-noise ratio for the parameters: noise bandwidth, spatial frequency content and rate of movement of patterns. In both normal and lesioned cats a broadband noise was found to be most effective in masking the large patterns while two other types of noise, a medium frequency noise and a high frequency noise had little or no masking effect. For recognition of the smaller patterns in normal cats the medium fre…
Improving Isolation of Blindly Separated Sources Using Time-Frequency Masking
2008
A refinement technique based on time-frequency masking is proposed to improve source isolation in blind audio source separation algorithms. The refinement technique uses an energy-normalized source-to-interference ratio in order to identify and eliminate interfering energy from the extracted sources. Some examples using this refinement method with different separation algorithms are discussed. The results show that source isolation can be significantly enhanced with negligible degradation of the separated sources.
Short baseline line matching for central imaging systems
2012
We develop a generic line matching method especially applicable to omnidirectional images taken from constructed scenes with short baseline motion where the motion of the imaging system between two views is mainly an arbitrary rotation and the translation of the camera between two views with respect to its distance to the imaged scene is negligible. We start by studying the relationship between images of lines on unitary sphere followed by proposing a simple algorithm for simultaneously matching vanishing points and lines. The developed algorithm is very simple, yet it works on images captured by all types of central imaging systems, including perspective, fish-eye and catadioptric images. …
A new minimum spanning tree-based method for shape description and matching working in Discrete Cosine space
2009
In this article, a new minimum spanning tree-based method for shape description and matching is proposed. Its properties are checked through the problem of graphical symbols recognition. Recognition invariance in front shift and multi-oriented noisy objects was studied in the context of small and low resolution binary images. The approach seems to have many desirable properties, even if the construction of graphs induces an expensive algorithmic cost. In order to reduce time computing, an alternative solution based on image compression concepts is provided. The recognition is realized in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discuss…
Towards a real-time 3D shape reconstruction using a structured light system
2005
This paper deals with 3D shape reconstruction using a structured light system (SLS) which projects a matrix of laser rays onto the scene to be analyzed. The intrinsic problem of such a system is the correspondence problem solving, which in this particular case amounts to matching up the imaged spots and the originating laser rays. In this paper, we propose a method for automatically obtaining configurations of the system (COS) (i.e. the relative positions of the camera, laser projector, and measuring scene) that permit to achieve a direct and unambiguous correspondence. After, we propose a splitting cell algorithm, which efficiently performs a real-time correspondence procedure. Experimenta…
Fuzzy Fusion in Multimodal Biometric Systems
2007
Multimodal authentication systems represent an emerging trend for information security. These systems could replace conventional mono-modal biometric methods using two or more features for robust biometric authentication tasks. They employ unique combinations of measurable physical characteristics: fingerprint, facial features, iris of the eye, voice print, hand geometry, vein patterns, and so on. Since these traits are hardly imitable by other persons, the aim of these multibiometric systems is to achieve a high reliability to determine or verify person's identity. In this paper a multimodal biometric system using two different fingerprints is proposed. The matching module integrates fuzzy…
Real Time Stereo Matching Using Two Step Zero-Mean SAD and Dynamic Programing
2018
Dense depth map extraction is a dynamic research field in a computer vision that tries to recover three-dimensional information from a stereo image pair. A large variety of algorithms has been developed. The local methods based on block matching that are prevalent due to the linear computational complexity and easy implementation. This local cost is used on global methods as graph cut and dynamic programming in order to reduce sensitivity to local to occlusion and uniform texture. This paper proposes a new method for matching images based on a two-stage of block matching as local cost function and dynamic programming as energy optimization approach. In our work introduce the two stage of th…
Electrophysiological Correlates of Change Detection during Delayed Matching Task: A Comparison of Different References
2017
Detecting the changed information between memory representation and incoming sensory inputs is a fundamental cognitive ability. By offering the promise of excellent temporal resolution, event-related potential (ERP) technique has served as a primary tool for studying this process with reference of the linked mastoid (LM). However, given that LM may distort the ERP signals, it is still undetermined whether LM is the best reference choice. The goal of the current study was to systematically compare LM, reference electrode standardization technique (REST) and average reference (AR) for assessing the ERP correlates of change detection during a delayed matching task. Colored shapes were adopted …