On image segmentation using information theoretic criteria

Image segmentation is a long-studied and important problem in image processing. Different solutions have been proposed, many of which follow the information theoretic paradigm. While these information theoretic segmentation methods often produce excellent empirical results, their theoretical properties are still largely unknown. The main goal of this paper is to conduct a rigorous theoretical study into the statistical consistency properties of such methods. To be more specific, this paper investigates if these methods can accurately recover the true number of segments together with their true boundaries in the image as the number of pixels tends to infinity. Our theoretical results show that both the Bayesian information criterion (BIC) and the minimum description length (MDL) principle can be applied to derive statistically consistent segmentation methods, while the same is not true for the Akaike information criterion (AIC). Numerical experiments were conducted to illustrate and support our theoretical findings.Comment: Published in at http://dx.doi.org/10.1214/11-AOS925 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

An MDL approach to the climate segmentation problem

This paper proposes an information theory approach to estimate the number of changepoints and their locations in a climatic time series. A model is introduced that has an unknown number of changepoints and allows for series autocorrelations, periodic dynamics, and a mean shift at each changepoint time. An objective function gauging the number of changepoints and their locations, based on a minimum description length (MDL) information criterion, is derived. A genetic algorithm is then developed to optimize the objective function. The methods are applied in the analysis of a century of monthly temperatures from Tuscaloosa, Alabama.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS289 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Reliable and robust molecular sexing of the hen harrier (Circus cyaneus) using PCR-RFLP of the CHD1 gene

The hen harrier (Circus cyaneus) is a bird of prey that is persecuted in the United Kingdom, and there is a need for a DNA-based individual identification and sexing system for the use in forensic investigations. This study reports a new set of PCR primers for the chromo-helicase-DNA-binding protein 1 gene, which allows sexing using PCR-RFLP. Instead of exonic primers that amplify across a large intron, this set consists of a primer within the intron, enabling reduction in amplicon sizes from 356 to 212 bp and 565 to 219 bp in W and Z chromosomes. DNA degradation and dilution experiments demonstrate that this set is significantly more robust than one that amplifies across the intron, and sequencing of the intronic primer-binding region across several individuals shows that it is highly conserved. While our objective is to incorporate this primer set into an STR-based individualization kit, it may in the meantime prove useful in forensic or conservation studies

Macro aerodynamic devices controlled by micro systems

Micro-ElectroMechanical-Systems (MEMS) have emerged as a major enabling technology across the engineering disciplines. In this study, the possibility of applying MEMS to the aerodynamic field was explored. We have demonstrated that microtransducers can be used to control the motion of a delta wing in a wind tunnel and can even maneuver a scaled aircraft in flight tests. The main advantage of using micro actuators to replace the traditional control surface is the significant reduction of radar cross-sections. At a high angle of attack, a large portion of the suction loading on a delta wing is contributed by the leading edge separation vortices which originate from thin boundary layers at the leading edge. We used microactuators with a thickness comparable to that of the boundary layer in order to alter the separation process and thus achieved control of the global motion by minute perturbations

Automatic estimation of flux distributions of astrophysical source populations

In astrophysics a common goal is to infer the flux distribution of populations of scientifically interesting objects such as pulsars or supernovae. In practice, inference for the flux distribution is often conducted using the cumulative distribution of the number of sources detected at a given sensitivity. The resulting "$\log(N>S)$-$\log (S)$" relationship can be used to compare and evaluate theoretical models for source populations and their evolution. Under restrictive assumptions the relationship should be linear. In practice, however, when simple theoretical models fail, it is common for astrophysicists to use prespecified piecewise linear models. This paper proposes a methodology for estimating both the number and locations of "breakpoints" in astrophysical source populations that extends beyond existing work in this field. An important component of the proposed methodology is a new interwoven EM algorithm that computes parameter estimates. It is shown that in simple settings such estimates are asymptotically consistent despite the complex nature of the parameter space. Through simulation studies it is demonstrated that the proposed methodology is capable of accurately detecting structural breaks in a variety of parameter configurations. This paper concludes with an application of our methodology to the Chandra Deep Field North (CDFN) data set.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS750 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org