Jesus Carlos Pedraza-Ortega

Development of a robotic FD-CT-guided navigation system for needle placement-preliminary accuracy tests.

A needle placement system using a serial robot arm for manipulation of biopsy and/or treatment needles is introduced. A method for fast calibration of the robot and the preliminary accuracy tests of the robotic system are presented.

Modeling Key Parameters for Greenhouse Using Fuzzy Clustering Techniques

The clustering techniques are usually used in classification and pattern recognition. Moreover, fuzzy logic is used for system modeling when the information is scarce, inaccurate or its behavior is described using a complex mathematical model. As example of this type of system, a greenhouse is considered, where the variables are: in-house and out-house temperature, humidity for both inside and outside the greenhouse and wind direction. These variables show a dynamic and non-linear behavior; being the in-house temperature and internal humidity the variables of concern for the greenhouse control and modeling. In this project, the development and implementation of three clustering algorithms, being fuzzy K-means, Fuzzy C-means and fuzzy clustering subtractive, is presented. This project is used as the foundation for the design of fuzzy systems and its application in temperature and humidity modeling of a greenhouse used as a laboratory of biotronics at the Universidad Autonoma de Queretaro.

A Profilometric Approach for 3D Reconstruction Using Fourier and Wavelet Transforms

In this research, an improved method for three-dimensional shape measurement by fringe projection is presented. The use of Fourier and Wavelet transform based analysis to extract the 3D information from the objects is proposed. The method requires a single image which contains a sinusoidal white light fringe pattern projected on it. This fringe pattern has a known spatial frequency and this information is used to avoid the discontinuities in the fringes with high frequency. Several computer simulations and experiments have been carried out to verify the analysis. The comparison between numerical simulations and experiments has proved the validity of this proposed method.

A 3D Sensor Based on a Profilometrical Approach

An improved method which considers the use of Fourier and wavelet transform based analysis to infer and extract 3D information from an object by fringe projection on it is presented. This method requires a single image which contains a sinusoidal white light fringe pattern projected on it, and this pattern has a known spatial frequency and its information is used to avoid any discontinuities in the fringes with high frequency. Several computer simulations and experiments have been carried out to verify the analysis. The comparison between numerical simulations and experiments has proved the validity of this proposed method.

FPGA-based architecture for real-time data reduction of ultrasound signals.

This paper describes a novel method for on-line real-time data reduction of radiofrequency (RF) ultrasound signals. The approach is based on a field programmable gate array (FPGA) system intended mainly for steel thickness measurements. Ultrasound data reduction is desirable when: (1) direct measurements performed by an operator are not accessible; (2) it is required to store a considerable amount of data; (3) the application requires measuring at very high speeds; and (4) the physical space for the embedded hardware is limited. All the aforementioned scenarios can be present in applications such as pipeline inspection where data reduction is traditionally performed on-line using pipeline inspection gauges (PIG). The method proposed in this work consists of identifying and storing in real-time only the time of occurrence (TOO) and the maximum amplitude of each echo present in a given RF ultrasound signal. The method is tested with a dedicated immersion system where a significant data reduction with an average of 96.5% is achieved.

Simulation Methodology for Mechatronic Applications using Multilanguage Techniques

Abstract This paper presents a simulation methodology proposal, applying a multilanguage technique to simulate a mechatronic system. Firstly, a way to interact between two programming languages is presented, by taking advantage of each language to facilitate the development of a complex simulation tool. Later, the mechanical structure is obtained in VRML format. Next, special software is used to compute the mathematical model for kinematics and dynamic behavior. The results are showed by graphical simulation with Graphic Libraries support. Finally, the methodology is applied to flexible manipulator with one degree of freedom as study case, and the graphical simulation is presented.

Location of mammograms ROI's and reduction of false-positive

BACKGROUND AND OBJECTIVE There are many work related with segmentation techniques, including nearest neighbor algorithm, fuzzy rules, morphological filters, image entropy, thresholding, machine learning, wavelet analysis, and so on. Such methods carry out the segmentation, but take a lot of processing time by modifying the content of the image or showing discern problems in homogeneous areas, and the segmentation technique is designed to work efficiently only with the techniques used. In this paper a method to segment mammograms in order to separate breast area from pectoral-muscle avoiding bright areas that produce noise and therefore reducing false-positives is presented. METHODS The proposed methodology is divided into four sections: 1) Pre-processing to acquire image and decreasing its size. 2) Improving the image quality through image thresholding and histogram equalization. 3) Localization of regions of interest (ROI) applying Scale-Invariant Feature Transform to find images descriptors. Clustering methods were implemented to determine the best number of clusters and which of these represent the most significant breast area. Then found ROIs coordinates are compared with the position of abnormalities diagnosed by the Mammographic Image Analysis Society. 4) Microcalcifications (mcc) detection; wavelet transform is used, and to enhance its performance different high-pass filters and high-frequency emphasis filters are evaluated. Symlet wavelets: Sym8 and Sym16 were used with different decomposition level; images results from both processes are compared and only those elements in common are detected as microcalcifications. RESULTS Moreover, muscles remnants in the corners of the regions of interest were removed using fuzzy c-means clustering. The best results in terms of sensitivity (91.27), false-positives per image (80.25), and precision (74.38) are compared with previous work. CONCLUSIONS Results shows that the breast area can be discriminated from the pectoral-muscle by avoiding to work with brightness areas that produces false positives. Moreover, because the image size is reduced the computer processing time will be decreased. This segmentation stage can be an addition to mammograms analysis broadly, not only to find mcc but abnormalities such as circumscribed masses, speculated masses and architectural distortion. Also is useful to create automatically an unsupervised segmentation in mammograms without stage of training.

Alignment of the Measurement Scale Mark during Immersion Hydrometer Calibration Using an Image Processing System

The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer to the surface of the liquid where it is immersed by implementing image processing algorithms. This approach reduces the variability in the apparent mass determination during the hydrostatic weighing in the calibration process, therefore decreasing the relative uncertainty of calibration.

Dedicated feature descriptor for outdoor augmented reality detection

Stable augmented reality applications consist of an accurate registration supported by a robust tracking module. In outdoor locations, the changing environmental and light conditions compromise this tracking. Reliable descriptors under unsettled conditions are essential for this process. The most used descriptors have this distinctive capacity, but computers and mobile devices process them in a long time frame. This paper investigates a new lightweight environment dedicated descriptor (EDD) trained with a machine-learning algorithm. The descriptor analyzes the scene characteristics with elements that can be computed fast and that have distinctive information about the selected area. The complete descriptor is used for semantic feature extraction with the aid of a trained random forest classifier. The descriptor is compared with the most popular descriptors—with respect to speed, accuracy, and invariance to illumination changes, scale, affine transformation, and rotation—and the results show that it is faster and in most cases equally reliable .

Calibration of an optical stereo-tracker with a videometric system using the pair-point method for IGS

In various applications of computer vision, there is the need to calibrate the coordinate systems of different elements respect to one another in order to have a proper perspective of the objects in the scene. In the field of computer assisted surgery (CAS) we encounter this problem in many applications, like navigation of surgical tools, surgical robotics, etc. This paper proposes an estimate calibration by means of the extraction of points of a grid plane pattern and the pair point method getting a proper calibration of an optical stereo-tracker with a videometric system. As a result, we obtained a calibration that allows to track the pose of a webcam within the working space of a stereo-tracker. This procedure will allow us to use this method to calibrate different navigated tools that have a videometric system attached.