Mathematical Morphology Based on Linear Combined Metric Spaces on Z2 (Part I): Fast Distance Transforms

Mathematical Morphology (MM) is a general method for image processing based on set theory. The two basic morphological operators are dilation and erosion. From these, several non linear filters have been developed usually with polynomial complexity, and this because the two basic operators depend strongly on the definition of the structural element. Most efforts to improve the algorithm's speed for each operator are based on structural element decomposition and/or efficient codification.A new framework and a theoretical basis toward the construction of fast morphological operators (of zero complexity) for an infinite (countable) family of regular metric spaces are presented in work. The framework is completely defined by the three axioms of metric. The theoretical basis here developed points out properties of some metric spaces and relationships between metric spaces in the same family, just in terms of the properties of the four basic metrics stated in this work. Concepts such as bounds, neighborhoods and contours are also related by the same framework.The presented results, are general in the sense that they cover the most commonly used metrics such as the chamfer, the city block and the chess board metrics. Generalizations and new results related with distances and distance transforms, which in turn are used to develop the morphologic operations in constant time, in contrast with the polynomial time algorithms are also given.     

Intelligent Assistance in Authoring Dynamically Generated Web Interfaces

Since its emergence in the early 1990s, the WWW has become not only an information system of unprecedented size, but a universal platform for the development of services and applications. However, most of the advances in web technologies are intended for professional developers, paying poor attention to end-users with no programming abilities but with explicit needs of creating and customizing web-based presentations. This provides a strong motivation for end-users to act as designers at some point, leading to an emerging role of new computing-related professionals to be considered. This paper is an effort to leverage such difficulties by providing intelligent mechanism to assist end-users in web-based authoring tasks. To carry out such a challenge, intelligent user-monitoring techniques are exploited to obtain high-level information that will be used to infer the user’s preferences and assist him throughout the interaction. Furthermore, we report on how iteration patterns can be applied to avoid repetitive tasks that are automatically carried out on behalf of the user. In order to bring off a feasible trade-off between expressivity and ease of use, a user experiment to obtain the user’s perception and evaluate the hit-rate of our system is also presented.     

Diagnosis of lung nodule using Moran’s index and Geary’s coefficient in computerized tomography images

This paper analyzes the application of Moran’s index and Geary’s coefficient to the characterization of lung nodules as malignant or benign in computerized tomography images. The characterization method is based on a process that verifies which combination of measures, from the proposed measures, has been best able to discriminate between the benign and malignant nodules using stepwise discriminant analysis. Then, a linear discriminant analysis procedure was performed using the selected features to evaluate the ability of these in predicting the classification for each nodule. In order to verify this application we also describe tests that were carried out using a sample of 36 nodules: 29 benign and 7 malignant. A leave-one-out procedure was used to provide a less biased estimate of the linear discriminator’s performance. The two analyzed functions and its combinations have provided above 90% of accuracy and a value area under receiver operation characteristic (ROC) curve above 0.85, that indicates a promising potential to be used as nodules signature measures. The preliminary results of this approach are very encouraging in characterizing nodules using the two functions presented.

Dissimilarity-based classification of chromatographic profiles

This paper proposes a non-parametric method for the classification of thin-layer chromatographic (TLC) images from patterns represented in a dissimilarity space. Each pattern corresponds to a mixture of Gaussian approximation of the intensity profile. The methodology comprises various phases, including image processing and analysis steps to extract the chromatographic profiles and a classification phase to discriminate among two groups, one corresponding to normal cases and the other to three pathological classes. We present an extensive study of several dissimilarity-based approaches analysing the influence of the dissimilarity measure and the prototype selection method on the classification performance. The main conclusions of this paper are that, Match and Profile-difference dissimilarity measures present better results, and a new prototype selection methodology achieves a performance similar or even better than conventional methods. Furthermore, we also concluded that simplest classifiers, such as k-NN and linear discriminant classifiers (LDCs), present good performance being the overall classification error less than 10% for the four-class problem.     

Device for characterization of thermal effusivity of liquids using photothermal beam deflection

We propose and study a novel optoelectronic device for thermal characterization of materials. It is based on monitoring the photothermal deflection of a laser beam within a slab of a thermo-optic material in thermal contact with the sample under study. An optical angle sensor is used to measure the laser deflection providing a simple and experimental arrangement. We demonstrate its principle and a simple procedure to measure thermal effusivity of liquids. The proposed device could be implemented into a compact sensor head for remote measurements using electrical and fiber optic links.     

An Approach for Recovering Distributed System Architectures

Reasoning about software systems at the architectural level is key to effective software development, management, evolution and reuse. All too often, though, the lack of appropriate documentation leads to a situation where architectural design information has to be recovered directly from implemented software artifacts. This is a very demanding process, particularly when involving recovery of runtime abstractions (clients, servers, interaction protocols, etc.) that are typical to the design of distributed software systems. This paper presents an exploratory reverse engineering approach, called X-ray, to aid programmers in recovering architectural runtime information from a distributed system's existing software artifacts. X-ray comprises three domain-based static analysis techniques, namely component module classification, syntactic pattern matching, and structural reachability analysis. These complementary techniques can facilitate the task of identifying a distributed system's implemented executable components and their potential runtime interconnections. The component module classification technique automatically distinguishes source code modules according to the executables components they implement. The syntactic pattern matching technique in turn helps to recognise specific code fragments that may implement typical component interaction features. Finally, the structural reachability analysis technique aids in the association of those features to the code specific for each executable component. The paper describes and illustrates the main concepts underlying each technique, reports on their implementation as a suit of new and off-the-shelf tools, and, to give evidence of the utility of the approach, provides a detailed account of a successful application of the three techniques to help recover a static approximation of the runtime architecture for Field, a publicly-available distributed programming environment.     

Advanced and Intelligent Control Techniques Applied to the Drive Control and Path Tracking Systems on a Robotic Wheelchair

This paper presents the theoretical support and experimental results of the application of advanced and intelligent control techniques to the drive control and trajectory tracking systems on a robotic wheelchair. The adaptive optimal control of the differential drive helps to improve the automatic guidance system's safety and comfort taking into consideration operating conditions such as load and distribution changes or motion actuator limitations. Furthermore, the incorporation of an optimal controller to minimize location errors and a fuzzy controller to adapt the linear velocity to the characteristics of the trajectory, provide the vehicle with a high degree of intelligence and autonomy, even when faced with obstacles. The global control solution implemented increases the features of the wheelchair for handicapped people, especially for those with a high degree of disability.     

CASANDRA: a prototype implementation of a system of network progressive transmission of medical digital images

In this paper, a prototype for progressive transmission of medical digital 2D images through the network, called CASANDRA, is presented. The prototype consists of the server part and the client part. In the server part, the images are acquired, stored, computed their wavelet transform and the wavelet coefficients stored, then transmitted progressively, when required, via TCP to the client. In the client part, with the inverse wavelet transform, the received wavelet coefficients are used to build successive improved reconstructions of the image.This prototype has been implemented and is being tested in the Radiotherapy Service of the Valencia University Hospital (Valencia, Spain).     

Guidance of a mobile robot using an array of static cameras located in the environment

This paper presents a new proposal for positioning and guiding mobile robots in indoor environments. The proposal is based on the information provided by static cameras located in the movement environment. This proposal falls within the scope of what are known as intelligent environments; in this case, the environment is provided with cameras that, once calibrated, allow the position of the robots to be obtained. Based on this information, control orders for the robots can be generated using a radio frequency link. In order to facilitate identification of the robots, even under extremely adverse ambient lighting conditions, a beacon consisting of four circular elements constructed from infrared diodes is mounted on board the robots. In order to identify the beacon, an edge detection process is carried out. This is followed by a process that, based on the algebraic distance, obtains the estimated ellipses associated with each element of the beacon. Once the beacon has been identified, the coordinates of the centroids for the elements that make up the beacon are obtained on the various image planes. Based on these coordinates, an algorithm is proposed that takes into account the standard deviation of the error produced in the various cameras in ascertaining the coordinates of the beacon’s elements. An odometric system is also used in guidance that, in conjunction with a Kalman Filter, allows the position of the robot to be estimated during the time intervals required to process the visual information provided by the cameras.