This paper describes the design and development of a Graphical User Interface through the virtual instrumentation software NI LabVIEW using the VISA function, to graphically visualize and storage the data of the climatological variables of temperature and relative humidity. The graphical interface offers the option to export the date, time and data of the two variables to text documents with extension “.txt”, which acquires the information of the electronic board wireless monitoring and control, which uses a main device PIC16F877A microcontroller. AMT1001 Precision Analog Sensor was used to sense temperature and relative humidity. The PIC16F877A was programmed using a C programming language in the CCS Compiler compiler, to the data acquisition, and send it via RS232 communication to the computer, using the PL2303 module USB to TTL converter. To check the GUI operation, the electronic wireless monitoring and control card was connected to the computer equipment by wire, however, the monitoring of the climate variables can be done wirelessly by XBEE technology. Future work aims to monitor the climate of a horticultural greenhouse with XBBE technology, so that the data is sent wirelessly to a computer that has the GUI, and is also connected to Ethernet or WIFI, which will have the LabVIEW graphical interface explained in this article, and the data will be displayed / analyzed through the internet.

In this paper, a new framework for iterative speckle noise reduction in polarimetric synthetic aperture radar (Pol)(SAR) data is introduced. Speckle is inherent to all coherent imaging systems and affects SAR imagery in the form of strong intensity variations in pixels with similar backscattering coefficients. This makes the interpretation of SAR data in several applications a difficult task. The proposed framework includes a pre-processing step capable of dealing with noise correlation usually found in single-look data. The general filtering approach is based on the Beltrami flow for de-noising manifolds or images painted on manifolds. The principal contribution of this work is to adapt this approach to deal with covariance or coherency matrices instead of optical imagery. The evaluation presented suggest that this approach allows for good spatial and radiometric preservation compared to other state of the art methods. Experiments are performed on the basis of synthetic and real world experimental data. The validation of the proposed framework is accomplished using two refined error performance measures and the well known effective number of looks (ENL) measured. The source code of a parallel implementation of the proposed framework is released under the MPL 2.0 1 alongside this paper.

Floodings in Mexico generated economic and human losses in recent years, so it is necessary to use all possible tools that can help the government to reduce all these disasters, especially human losses. Therefore, a Graphical User Interface (GUI) was developed in Matlab for the segmentation and classification of vegetation, water and city in multispectral images obtained from the Landsat 8 satellite with the intention of detecting floods and vulnerable zones of flooding. The interface performs a feature extraction, segmentation, classification, validation and visualization of the final results obtained through basic segmentation algorithms such as the Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), in addition to performing the segmentation with one of the artificial intelligence methodologies most used in the state of the art: support vector machine (SVM) and the proposal of SVM with the k-nearest neighbors as an improvement to the algorithm.

Resumen. El presente artículo analiza una serie de métodos para el procesamiento de imágenes de personas, con el fin de segmentar su piel. La base de datos Jochen Triesch Static Hand Posture Database [9] proporciona una amplia gama de tonalidades de piel, obtenida de personas de razas y edades distintas. Las tareas de detección de piel en imágenes se enfrentan a diversos retos, debido a factores diversos como: variaciones en la iluminación, factores ambientales y fondo de la escena. En este trabajo se muestran los resultados obtenidos al desarrollar algoritmos de segmentación basados en distintas técnicas heurísticas y probabilísticas, a partir de la utilización de una base de datos en el espacio de color RGB.

In recent years the floods in Mexico caused economic and human losses, therefore, it is necessary to use the possible tools that can provide help to the government to reduce damage from natural disasters. For this, we decided to develop a graphical user interface, known as GUI in Matlab for the segmentation of SAR, Multispectral and POLSAR images, with the intention of detecting flooding and vulnerable areas to flooding. The designed software compute a rivers segmentation in order to make the comparison between image with flooding and the image without flooding from the same area, and to obtain a visually result where a projection of the vulnerable areas to flooding in the original image this with help of basic segmentation algorithms such as grayscale, binarization, dilation, wavelet, normalization, filtering and edge detection.