CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

IFTrace: Video segmentation of deformable objects using the Image Foresting Transform

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Systematic analysis of the Fourier transform spectrum of (CH3OH)-C-13 between 400 and 950 cm(-1)

We have investigated a high-resolution Fourier transform (FT) absorption spectrum of the (CH3OH)-C-13 isotopomer of methanol from 400 to 950 cm(-1) with the Ritz program. We present the assignments of 7160 transitions, 3021 of which belong to Asymmetry, and 4139 to E-symmetry. These transitions occur between states labeled by K quantum numbers up to 14, and by torsional quantum numbers n up to 4. The Ritz program evaluated the energies of the 4684 involved levels with an accuracy of the order of 10(-4) cm(-1). All of the assigned lines correspond to transitions involving torsionally excited levels within the ground small-amplitude vibrational state. (c) 2005 Elsevier B.V. All rights reserved.

Assessment of maturity degree of composts from domestic solid wastes by fluorescence and fourier transform infrared spectroscopies

Methods of assessment of compost maturity are needed so the application of composted materials to lands will provide optimal benefits. The aim of the present paper is to assess the maturity reached by composts from domestic solid wastes (DSW) prepared under periodic and permanent aeration systems and sampled at different composting time, by means of excitation-emission matrix (EEM) fluorescence spectroscopy and Fourier transform infrared spectroscopy (FT-IR). EEM spectra indicated the presence of two different fluorophores centered, respectively, at Ex/Em wavelength pairs of 330/425 and 280/330 nm. The fluorescence intensities of these peaks were also analyzed, showing trends related to the maturity of composts. The contour density of EEM maps appeared to be strongly reduced with composting days. After 30 and 45 days of composting, FT-IR spectra exhibited a decrease of intensity of peaks assigned to polysaccharides and in the aliphatic region. EEM and FT-IR techniques seem to produce spectra that correlate with the degree of maturity of the compost. Further refinement of these techniques should provide a relatively rapid method of assessing the suitability of the compost to land application.

DIODE-LASER AND FOURIER-TRANSFORM SPECTROSCOPY OF THE (CH3OH)-C-13 C-O STRETCHING MODE

In this work we present high resolution Doppler limited absorption spectra measurements of the C-O stretching mode of (CH3OH)-C-13, obtained from diode laser spectroscopy, and the Fourier Transform spectrum obtained at 0. 12 cm-1 resolution. By using these data and previously known spectroscopic information, we determined the frequency and the J quantum number for the multiplets of the P and R(J) branches of the C-O stretching fundamental band. Infrared transitions in coincidence with emission lines of the regular CO2 laser and some of its isotope parents are pointed out.

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

Symmetry transform in Faddeev-Jackiw quantization of dual models

We study the presence of symmetry transformations in the Faddeev-Jackiw approach for constrained systems. Our analysis is based in the case of a particle submitted to a particular potential which depends on an arbitrary function. The method is implemented in a natural way and symmetry generators are identified. These symmetries permit us to obtain the absent elements of the sympletic matrix which complement the set of Dirac brackets of such a theory. The study developed here is applied in two different dual models. First, we discuss the case of a two-dimensional oscillator interacting with an electromagnetic potential described by a Chern-Simons term and second the Schwarz-Sen gauge theory, in order to obtain the complete set of non-null Dirac brackets and the correspondent Maxwell electromagnetic theory limit. ©1999 The American Physical Society.

Common architecture for discrete wavelet transform analysis and synthesis with sequential and constant processing elements

This paper adresses the problem on processing biological data such as cardiac beats, audio and ultrasonic range, calculating wavelet coefficients in real time, with processor clock running at frequency of present ASIC's and FPGA. The Paralell Filter Architecture for DWT has been improved, calculating wavelet coefficients in real time with hardware reduced to 60%. The new architecture, which also processes IDWT, is implemented with the Radix-2 or the Booth-Wallace Constant multipliers. Including series memory register banks, one integrated circuit Signal Analyzer, ultrasonic range, is presented.

Discrete wavelet transform signal analyzer

This paper addresses the problem of processing biological data, such as cardiac beats in the audio and ultrasonic range, and on calculating wavelet coefficients in real time, with the processor clock running at a frequency of present application-specified integrated circuits and field programmable gate array. The parallel filter architecture for discrete wavelet transform (DWT) has been improved, calculating the wavelet coefficients in real time with hardware reduced up to 60%. The new architecture, which also processes inverse DWT, is implemented with the Radix-2 or the Booth-Wallace constant multipliers. One integrated circuit signal analyzer in the ultrasonic range, including series memory register banks, is presented. © 2007 IEEE.

Microcalcification enhancement and classification on mammograms using the wavelet transform

This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency subband it's possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm. © 2008 IEEE.

HTS: A new shape descriptor based on Hough Transform

In this paper we propose a novel method for shape analysis called HTS (Hough Transform Statistics), which uses statistics from Hough Transform space in order to characterize the shape of objects in digital images. Experimental results showed that the HTS descriptor is robust and presents better accuracy than some traditional shape description methods. Furthermore, HTS algorithm has linear complexity, which is an important requirement for content based image retrieval from large databases. © 2013 IEEE.

Análise da saliva de pacientes com ardência bucal por espectroscopia de Fourier Transform Infrared (FT-IR)

Pós-graduação em Biopatologia Bucal - ICT