Search results for "Image processing"
showing 10 items of 3285 documents
Ridge-line optimal detector
2000
Image processing techniques have seen many developments in recent years. Starting from the pioneering work of Canny, Deriche developed a second order recursive filter capable of detecting stepped contours. However, there are other contour shapes that those filters struggle to detect. We describe a new optimal filter sensu Canny for detecting ridge-line contours. This is a third order recursive and even filter. It is dependent on three parameters by which detection accuracy is adjusted. The results obtained by applying this filter to (possibly noise- affected) images are compared with those in the work by Ziou. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)00706-6)
BioImageXD - Free Microscopy Image Processing Software
2008
Extended abstract of a paper presented at Microscopy and Microanalysis 2008 in Albuquerque, New Mexico, USA, August 3 – August 7, 2008
Reduction of the number of spectral bands in Landsat images: a comparison of linear and nonlinear methods
2006
We describe some applications of linear and nonlinear pro- jection methods in order to reduce the number of spectral bands in Land- sat multispectral images. The nonlinear method is curvilinear component analysis CCA, and we propose an adapted optimization of it for image processing, based on the use of principal-component analysis PCA, a linear method. The principle of CCA consists in reproducing the topol- ogy of the original space projection points in a reduced subspace, keep- ing the maximum of information. Our conclusions are: CCA is an im- provement for dimension reduction of multispectral images; CCA is really a nonlinear extension of PCA; CCA optimization through PCA called CCAinitP…
Automatic Image Annotation Using Random Projection in a Conceptual Space Induced from Data
2018
The main drawback of a detailed representation of visual content, whatever is its origin, is that significant features are very high dimensional. To keep the problem tractable while preserving the semantic content, a dimen- sionality reduction of the data is needed. We propose the Random Projection techniques to reduce the dimensionality. Even though this technique is sub-optimal with respect to Singular Value Decomposition its much lower computational cost make it more suitable for this problem and in par- ticular when computational resources are limited such as in mobile terminals. In this paper we present the use of a "conceptual" space, automatically induced from data, to perform automa…
Calibration of a three-dimensional reconstruction system using a structured light source
2002
We present a method for calibrating a range finder system composed of a camera and a structured light source. The system is used to reconstruct the three-dimensional (3-D) surface of an object. This is achieved by projecting a pattern, represented by a set of regularly spaced spots, on the surface of the object using the structured light source. An image of the illuminated object is next taken and by analyzing the distortion of the projected pattern, the 3-D surface of the object can be reconstructed. This reconstruction operation can be envisaged only if the system is calibrated. Instead of using a classical calibration method, which is based on the determination of the matrices that chara…
DSMAV: An improved solution for multi-attribute search based on load capacities
2016
DHT (Distributed Hash Table) such as CHORD or PARTRY facilitates information searching in scalable systems. Two popular DHT-based approaches for range or multi-attribute search are to rely on attribute-value tree and a combination of attributes and values. However, tradeoff between a load balancing mechanism and query efficiency is a challenging task for such information searching systems. In this paper, we propose improved algorithms for a system called DSMAV in which information resources are distributed fairly among nodes and found based on multi-attribute queries in a small number of hop counts. Our system creates identifiers from resource names, each of which is a combination of attrib…
SOM-Based Class Discovery for Emotion Detection Based on DEAP Dataset
2018
This paper investigates the possibility of identifying classes by clustering. This study includes employing Self-Organizing Maps (SOM) in identifying clusters from EEG signals that could then be mapped to emotional classes. Beginning by training varying sizes of SOM with the EEG data provided from the public dataset: DEAP. The produced graphs showing Neighbor Distance, Sample Hits, and Weight Position are examined. Following that, the ground-truth label provided in DEAP is tested, in order to identify correlations between the label and the clusters produced by the SOM. The results show that there is a potential of class discovery using SOM-based clustering. It is then concluded that by eval…
Maximizing reading: pattern analysis to describe points of gaze
2006
As people read texts, their points of gaze can be described either as a sequence or as a pattern of dots. If reading fixations are visualized as a pattern and their duration is graphically attributed to the 3 rd dimension, image processing techniques can be employed to describe individual reading styles. Two reader groups of text editors and of University students were matching according to parametric tests. Yet they appeared to have marked inter-subject variability of fixation distribution when individual cases were considered. To illustrate this, we applied a simple "Coulomb law" - like model that takes both fixation duration and spacing into account. Further the image entropy filter was …
CrowdVAS-Net: A Deep-CNN Based Framework to Detect Abnormal Crowd-Motion Behavior in Videos for Predicting Crowd Disaster
2019
With the increased occurrences of crowd disasters like human stampedes, crowd management and their safety during mass gathering events like concerts, congregation or political rally, etc., are vital tasks for the security personnel. In this paper, we propose a framework named as CrowdVAS-Net for crowd-motion analysis that considers velocity, acceleration and saliency features in the video frames of a moving crowd. CrowdVAS-Net relies on a deep convolutional neural network (DCNN) for extracting motion and appearance feature representations from the video frames that help us in classifying the crowd-motion behavior as abnormal or normal from a short video clip. These feature representations a…
Three-domain image representation for personal photo album management
2010
In this paper we present a novel approach for personal photo album management. Pictures are analyzed and described in three representation spaces, namely, faces, background and time of capture. Faces are automatically detected and rectified using a probabilistic feature extraction technique. Face representation is then produced by computing PCA (Principal Component Analysis). Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Temporal data is obtained through the extraction of EXIF (Exchangeable image file format) data. Each image in the collection is then automatically organized using a mean-shift clustering technique. While many system…