Plane-to-plane positioning from image-based visual servoing and structured light

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

Compression-based Image Registration

Image registration is an important component of image analysis used to align two or more images. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can maximally compress one image given the information in the other. The contribution of this paper is twofold. First, we show that the image registration process can be dealt with from the perspective of a compression problem. Second, we demonstrate that the similarity metric, introduced by Li et al., performs well in image registration. Two different versions of the similarity metric have been used: the Kolmogorov version, computed using standard real-world compressors, and the Shannon version, calculated from an estimation of the entropy rate of the images

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

An information theoretic framework for image segmentation

In this paper, an information theoretic framework for image segmentation is presented. This approach is based on the information channel that goes from the image intensity histogram to the regions of the partitioned image. It allows us to define a new family of segmentation methods which maximize the mutual information of the channel. Firstly, a greedy top-down algorithm which partitions an image into homogeneous regions is introduced. Secondly, a histogram quantization algorithm which clusters color bins in a greedy bottom-up way is defined. Finally, the resulting regions in the partitioning algorithm can optionally be merged using the quantized histogram

An empirical study of machine learning techniques applied to image watermarking

A study of how the machine learning technique, known as gentleboost, could improve different digital watermarking methods such as LSB, DWT, DCT2 and Histogram shifting.

Investment, duration, and exit strategies for corporate and independent venture capital-backed start-ups

We propose a model of investment, duration, and exit strategies for start-ups backed by venture capital (VC) funds that accounts for the high level of uncertainty, the asymmetry of information between insiders and outsiders, and the discount rate. Our analysis predicts that start-ups backed by corporate VC funds remain for a longer period of time before exiting and receive larger investment amounts than those financed by independent VC funds. Although a longer duration leads to a higher likelihood of an exit through an acquisition, a larger investment increases the probability of an IPO exit. These predictions find strong empirical support.

Positioning an underwater vehicle through image mosaicking

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle

Generating Brand Equity through Corporate Social Responsibility to Key Stakeholders

In this paper we argue that socially responsible policies have a positive impact on a firm's brand equity in the short-term as well as in the long-term. Moreover, once we distinguish between different stakeholders, we posit that secondary stakeholders such as community are even more important than primary stakeholders (customers, shareholders, workers and suppliers) in generating brand equity. Policies aimed at satisfied community interests act as a mechanism to reinforce trust that gives further credibility to social responsible polices with other stakeholders. The result is a decrease in conflicts among stakeholders and greater stakeholder willingness to provide intangible resources that enhance brand equity. We provide support of our theoretical contentions making use of a panel data composed of 57 firms from 10 countries (the US, Japan, South Korea, France, the UK, Italy, Germany, Finland, Switzerland and the Netherlands) for the period 2002 to 2007. We use detailed information on brand equity obtained from Interbrand and on corporate social responsibility (CSR) provided by the SiRi Global Profile database, as compiled by the Sustainable Investment Research International Company (SiRi).

Credit lines: The other side of corporate liquidity

In this paper we offer the first large sample evidence on the availability and usage ofcredit lines in U.S. public corporations and use it to re-examine the existing findings oncorporate liquidity. We show that the availability of credit lines is widespread and thataverage undrawn credit is of the same order of magnitude as cash holdings. We test thetrade-off theory of liquidity according to which firms target an optimum level of liquidity,computed as the sum of cash and undrawn credit lines. We provide support for the existenceof a liquidity target, but also show that the reasons why firms hold cash and credit linesare very different. While the precautionary motive explains well cash holdings, the optimumlevel of credit lines appears to be driven by the restrictions imposed by the credit line itself,in terms of stated purpose and covenants. In support to these findings, credit line drawdownsare associated with capital expenditures, acquisitions, and working capital.

Corporate finance and the monetary transmission mechanism

This paper analyzes the transmission mechanisms of monetarypolicy in a general equilibrium model of securities marketsand banking with asymmetric information. Banks' optimal asset/liability policy is such that in equilibrium capital adequacy constraints are always binding. Asymmetric information about banks' net worth adds a cost to outside equity capital, which limits the extent to which banks can relax their capital constraint. In this context monetarypolicy does not affect bank lending through changes in bank liquidity. Rather, it has the effect of changing theaggregate composition of financing by firms. The model also produces multiple equilibria, one of which displays all the features of a "credit crunch". Thus, monetary policy can also have large effects when it induces a shift from one equilibrium to the other.

Corporate criminal law and organization incentives: A managerial perspective

Corporate criminal liability puts a serious challenge to the economictheory of enforcement. Are corporate crimes different from other crimes?Are these crimes best deterred by punishing individuals, punishing corporations, or both? What is optimal structure of sanctions? Shouldcorporate liability be criminal or civil? This paper has two majorcontributions to the literature. First, it provides a common analyticalframework to most results presented and largely discussed in the field.In second place, by making use of the framework, we provide new insightsinto how corporations should be punished for the offenses committed bytheir employees.

Generating global brand equity through corporate social responsibility to key stakeholders

In this paper we argue that corporate social responsibility (CSR) to various stakeholders(customers, shareholders, employees, suppliers, and community) has a positive effect on globalbrand equity (BE). In addition, policies aimed at satisfying community interests help reinforcecredibility to social responsible polices with other stakeholders. We test these theoreticalcontentions using panel data comprised of 57 global brands originating from 10 countries (USA,Japan, South Korea, France, UK, Italy, Germany, Finland, Switzerland and the Netherlands) forthe period 2002 to 2008. Our findings show that CSR to each of the stakeholder groups has apositive impact on global BE. In addition, global brands that follow local social responsibilitypolicies over communities obtain strong positive benefits in terms of the generation of BE, as itenhances the positive effects of CSR to other stakeholders, particularly to customers. Therefore,for managers of global brands it is particularly productive for generating brand value to combineglobal strategies with the satisfaction of the interests of local communities.

Parallelizing remote sensing image geometric correction

Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.

Corporate governance and corporate social performance

By integrating the agency and stakeholder perspectives, this study aims to provide a systematic understanding of the firm- and institutional-level corporate governance factors that affect corporate social performance (CSP). We analyze a large global panel dataset and reveal that CSP is positively associated with board independence, but negatively with ownership concentration. These results underscore the idea that the benefits of CSP do not flow to shareholders to the same extent as the costs and that the allocation of resources to CSP is lower when shareholders are powerful. Furthermore, these findings indicate that independent directors should be understood as agents in their own right, not only focused on defending shareholder interests. We also find that CSP is negatively related to investor protection and shareholder-oriented environments, while it is positively related to egalitarian environments. Finally, we jointly analyze firm-level drivers and institutional contexts.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.