Search results for "RECOGNITION"
showing 10 items of 3607 documents
Randomized Hough Transform for Ellipse Detection with Result Clustering
2005
Our research is focused on the development of robust machine vision algorithms for pattern recognition. We want to provide robotic systems the ability to understand more on the external real world. In this paper, we describe a method for detecting ellipses in real world images using the randomized Hough transform with result clustering. A preprocessing phase is used in which real world images are transformed - noise reduction, greyscale transform, edge detection and final binarization - in order to be processed by the actual ellipse detector. The ellipse detector filters out false ellipses that may interfere with the final results. Due to the fact that usually more "virtual" ellipses are de…
Three-dimensional object detection under arbitrary lighting conditions
2006
A novel method of 3D object recognition independent of lighting conditions is presented. The recognition model is based on a vector space representation using an orthonormal basis generated by the Lambertian reflectance functions obtained with distant light sources. Changing the lighting conditions corresponds to multiplying the elementary images by a constant factor and because of that, all possible lighting views will be elements that belong to that vector space. The recognition method proposed is based on the calculation of the angle between the vector associated with a certain illuminated 3D object and that subspace. We define the angle in terms of linear correlations to get shift and i…
Three-dimensional object recognition by Fourier transform profilometry
2008
An automatic method for three-dimensional (3-D) shape recognition is proposed. It combines the Fourier transform profilometry technique with a real-time recognition setup such as the joint transform correlator (JTC). A grating is projected onto the object surface resulting in a distorted grating pattern. Since this pattern carries information about the depth and the shape of the object, their comparison provides a method for recognizing 3-D objects in real time. A two-cycle JTC is used for this purpose. Experimental results demonstrate the theory and show the utility of the new proposed method.
SmartSpectra: Applying multispectral imaging to industrial environments
2005
SmartSpectra is a smart multispectral system for industrial, environmental, and commercial applications where the use of spectral information beyond the visible range is needed. The SmartSpectra system provides six spectral bands in the range 400-1000nm. The bands are configurable in terms of central wavelength and bandwidth by using electronic tunable filters. SmartSpectra consists of a multispectral sensor and the software that controls the system and simplifies the acquisition process. A first prototype called Autonomous Tunable Filter System is already available. This paper describes the SmartSpectra system, demonstrates its performance in the estimation of chlorophyll in plant leaves, …
Probing neural mechanisms of music perception, cognition, and performance using multivariate decoding.
2012
Recent neuroscience research has shown increasing use of multivariate decoding methods and machine learning. These methods, by uncovering the source and nature of informative variance in large data sets, invert the classical direction of inference that attempts to explain brain activity from mental state variables or stimulus features. However, these techniques are not yet commonly used among music researchers. In this position article, we introduce some key features of machine learning methods and review their use in the field of cognitive and behavioral neuroscience of music. We argue for the great potential of these methods in decoding multiple data types, specifically audio waveforms, e…
Face Processing on Low-Power Devices
2009
The research on embedded vision-based techniques is considered nowadays as one of the most interesting matters of computer vision. In this work we address the scenario in which a real-time face processing system is needed to monitor people walking through some locations. Some face detection (e.g., Viola-Jones face detector) and face recognition (e.g., eigenfaces) approaches have reached a certain level of maturity, so we focused on the development of such techniques on embedded systems taking into account both hardware and software constraints. Our goal is to detect the presence of some known individuals inside some sensitive areas producing a compact description of the observed people. Cap…
Robustly correlated key‐medical image for DNA‐chaos based encryption
2021
Abstract Medical images include confidential and sensitive information about patients. Hence, ensuring the security of these images is a crucial requirement. This paper proposes an efficient and secure medical image encryption‐decryption scheme based on deoxyribonucleic acid (DNA), one‐dimensional chaotic maps (tent and logistic maps), and hash functions (SHA‐256 and MD5). The first part of the proposed scheme is the key generation based on the hash functions of the image and its metadata. The key then is highly related and intensely sensitive to the original image. The second part is the rotation and permutation of the first two MSB bit‐plans of the medical image to reduce its black backgr…
Automatic Detection of Infantile Hemangioma using Convolutional Neural Network Approach
2020
Infantile hemangioma is the most common tumor of childhood. This study proposes an automatic detection as a preliminary step for a further accurate monitoring tool to evaluate the clinical status of hemangioma. For the detection of hemangioma pixels, a convolutional neural network (CNN) was trained on patches of two classes (hemangioma and nonhemangioma) from the train dataset, and then it was used to classify all the pixels of the region of interest from the test dataset. In order to evaluate the results of segmentation obtained with CNN, the region of interest of the test dataset was also segmented using two classical methods of segmentation: fuzzy c-means clustering (FCM) and segmentatio…
Trends in pattern recognition
1993
Aims of this paper are to present a short history of pattern recognition, its current areas of interest and future developments. The term pattern recognition is vague, its related topics including the study of sensorial stimuli, the analysis of physical phenomena and models of reasoning. Here we concentrate our attention on visual patterns and the machines that have been realized in order perform automatic pattern recognition. Some theoretical approaches will be also reviewed.
Fast algorithm for detection of reference spheres in digital panoramic radiography.
2009
In this paper, an algorithm for detection of reference spheres from digital panoramic radiographic images is presented. The proposed algorithm was tested on a database of 107 digital panoramic radiographic images which were used for dental diagnostics. Results show that the proposed method exhibits for detection of reference spheres, a sensitivity of 97.33% and specificity of 93.85%. Performance time differed between 0.55 and 2.36s depending on image size. The aim of this work was to provide a fast ellipse detection algorithm to reduce measuring time on preoperative implant planning by lowering the computational cost.