Search results for "Pattern Recognition"

Applying Wavelet Packet Decomposition and One-Class Support Vector Machine on Vehicle Acceleration Traces for Road Anomaly Detection

2013

Road condition monitoring through real-time intelligent systems has become more and more significant due to heavy road transportation. Road conditions can be roughly divided into normal and anomaly segments. The number of former should be much larger than the latter for a useable road. Based on the nature of road condition monitoring, anomaly detection is applied, especially for pothole detection in this study, using accelerometer data of a riding car. Accelerometer data were first labeled and segmented, after which features were extracted by wavelet packet decomposition. A classification model was built using one-class support vector machine. For the classifier, the data of some normal seg…

A kernel support vector machine based technique for Crohn’s disease classification in human patients

2017

In this paper a new technique for classification of patients affected by Crohn’s disease (CD) is proposed. The proposed technique is based on a Kernel Support Vector Machine (KSVM) and it adopts a Stratified K-Fold Cross-Validation strategy to enhance the KSVM classifier reliability. Traditional manual classification methods require radiological expertise and they usually are very time-consuming. Accordingly to three expert radiologists, a dataset composed of 300 patients has been selected for KSVM training and validation. Each patient was codified by 22 extracted qualitative features and classified as Positive or Negative as the related histological specimen result showed the CD. The eff…

Studies on the Effectiveness of Multispectral Images for Face Recognition: Comparative Studies and New Approaches

2013

In this paper, we investigate face recognition in unconstrained illumination conditions. A twofold contribution is proposed: First, three state of the art algorithms, namely Multiblock Local Binary Pattern (MBLBP), Histogram of Gabor Phase Patterns (HGPP) and Local Gabor Binary Pattern Histogram Sequence (LGBPHS) are challenged against the IRIS-M3 multispectral face data base to evaluate their robustness against high illumination variation. Second, we propose to enhance the Performance of the three mentioned algorithms, which has been drastically decreased because of the non-monotonic illumination variation that distinguishes the IRIS-M3 face database. Instead of the usual braod band images…

Improved locally adaptive least-squares detection of differences in images

2007

We introduce a method for change detection under nonuniform changes of intensity using an improved least-squares method. A locally adaptive normalizing window is correlated with the two images, and a morphological postprocessing is then applied to isolate objects that have been added or removed from the scene. We use a modification of the least-squares solution to get rid of clutter caused by intensity changes that do not satisfy the model assumed for the least-squares solution.

Extended scale-invariant pattern recognition with white-light illumination.

2000

A previous method of obtaining scale-invariance detection with white-light illumination has been improved on. We were able to detect different scaled versions of the target up to a magnification factor equal to 2. We simultaneously detected several versions in the same scene, because each scale factor is codified in a different wavelength. Experimental results demonstrate the proposed technique and show the utility of the method.

Real filter based on Mellin radial harmonics for scale-invariant pattern recognition.

1994

Several theoretical and experimental studies are developed in order to simplify the construction of filters based on Mellin radial harmonics (MRH) for scale-invariant pattern recognition. A real filter based on MRH is designed. The impulse response of the filter is a hermitic function, obtained by a suitable modification of a MRH component. This real filter has the same scale invariance as the conventional complex MRH filters, with the main advantage of its simplicity. Both computer simulations and optical experiments are presented.

Does signal detection methodology allow to measure discrimination, but not pain?

1979

A Windowing strategy for Distributed Data Mining optimized through GPUs

2017

Abstract This paper introduces an optimized Windowing based strategy for inducing decision trees in Distributed Data Mining scenarios. Windowing consists in selecting a sample of the available training examples (the window) to induce a decision tree with an usual algorithm, e.g., J48; finding instances not covered by this tree (counter examples) in the remaining training examples, adding them to the window to induce a new tree; and repeating until a termination criterion is met. In this way, the number of training examples required to induce the tree is reduced considerably, while maintaining the expected accuracy levels; which is paid in terms of time performance. Our proposed enhancements…

A comparative study of best spectral bands selection systems for face recognition

2014

Multispectral images (MI) have shown promising capabilities to solve problems resulting from high illumination variation in face recognition. However, the use of MI, with the huge number of captured spectral bands for each subject, is impractical unless a system for best spectral bands selection (BSBS) is used. In this work, first we give an up to date overview of the existing BSBS techniques proposed for face recognition. We aim to highlight the imporatnce of this component of MI based systems. The reviewed techniques are then experimented using the multispectral face database IRIS - M3 to compare their performances. To the best of our knowledge this is the first study that reviews and com…

Segmentation of Hyperspectral Images for the Detection of Rotten Mandarins

2008

The detection of rotten citrus in packing lines is carried out manually under ultraviolet illumination, which is dangerous for workers. Light emitted by the rotten region of the fruit due to the ultraviolet-induced fluorescence is used by the operator to detect the damages. This procedure is required because the low contrast between the damaged and sound skin under visible illumination difficult their detection. We study a set of techniques aimed to detect rottenness in citrususing visible and near infrared lighting trough an hyperspectral imaging system. Methods for selecting a proper set of wavelengths are investigated such as correlation analysis, mutual information, stepwise or genetic …