Numerical and Statistical tools for images analysis. based on the database from Frascati Tokamak Upgrade. Main System Skills

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1 Numerical and Statistical tools for images analysis based on the database from Frascati Tokamak Upgrade M. Chinnici a, S. Cuomo b, S. Migliori c a ENEA- FIM-INFOPPQ, Casaccia Research Center, Via Anguillarese 301, S.Maria di Galeria, Italy b UNIVERSITA FEDERICO II, Dipartimento di Matematica e Applicazioni R.Caccioppoli Via Cinthia Napoli, Italy c ENEA- FIM, Enea Sede, Lungotevere Thaon di Revel n Roma, Italy Introduction The advent of the internet and extensive digital image libraries has entailed the development of rapid and efficient computerbased image searching and browsing techniques. The term content-based image retrieval refers to automatic recovery of images from a database based on a set of graphic features that qualify the images and that are, loosely speaking, similar to the characteristics of a given query image. This contribution (within the CRESCO Project) concerns the application of retrieval techniques and analysis of plasma images coming from Frascati Tokamak Upgrade (FTU) (Fig.1). Data from FTU are acquired as movies or single frames. The wide number of information available by visual inspection of the data is often a limitation to real time experimental investigation. It appears that the images from the cameras can help to reconstruct some plasma phenomena and real time analysis could be useful for machine operation. On the other hand, due to the large number of data recorded, visual inspection of the movies is time consuming and often insufficient to correlate the images to other experimental findings. For a profitable use of the signals it is desirable to build specific tools for automatic processing of the images. The problems increases in complexity and cost in terms of hardware and software resources. In this research field the growing demand for computational resources has been a persistent goal of computational scientist. The challenge is to solve these problems with a computational power that could be achieved inexpensively with collection of distributed resources. The main goal is to provide both efficient and low cost computing environment by sharing of computational tools. This paper illustrates the acquisition system and the procedures developed for the processing and analysing of FTU images using ENEA-GRID technologies and middleware. In details, data are stored in a suitable database customize to FTU, to be adopt in mathematical and statistical models in order to correlate the images with plasma signals and to search the image information retrieval. Main System Skills The overall software system of FTU (Frascati Tokamak Upgrade) image analysis tool is organized by using open source software. The core of the applicative is a MySQL database (DB), data are stored in a suitable database customize to FTU, to be utilize in mathematical and statistical models both based in order to correlate the images with plasma signals and to search the image information retrieval. Being software development, the DB has been designed taking into that the number of operations on the images may depends on the analysis and the information retrials, and for this reason at each operation suitable performed in the data structure, IMAGE (Fig. 3). In order to better manage the operations on images, the system has been structured into classes: cam, folder, image (Fig. 4). The language chosen is object oriented C + +, as also to interface software with the database through the use of APIs MySQL + + (Fig.5.A- 5. B). In order to manipulate the informations inside the acquired images libraries of Image Magick open source software are used (conversion of an image scale Gray, creation, calculation and display of Histogram, etc...). Graphical libraries for data visualizations are also in our software system. Query q = conn >query(); try{ q << "CREATE TABLE IF NOT EXISTS `cams` (" << "`id_cam` varchar(20) NOT NULL," << "`type` varchar(1) NOT NULL," << "PRIMARY KEY (`id_cam`)" << ") ENGINE=InnoDB DEFAULT CHARSET=latin1;"; q.execute(); } catch(const BadQuery err_qry){ cerr << "Query error: " << err_qry.what() << endl; cout << "Creation table cams error." << endl; return false; } Fig.5.A : Piece of CAMS table code First results try{ q << "INSERT INTO `cams` (`id_cam`, `type`) VALUES" << "('" << name_cam << "', '" << cam_type << "');"; q.execute(); } catch(const BadQuery err_qry){ cout << "Insert item table cams error." << endl; return false; } Fig.5.B: Piece of code for filling CAMS table. The aim this section in the description of the software systems by means simple example. More image processing basics and data a- re developed in the system, here we not speak about it. In the following example, we show the conversion of a colour i- mage of FTU into a grey-scale image. Morever the gray-scale histogram graph is comptued and a suitable text file contain the numerical values. The system is organized in the way that the results of each operation are stored in folders that retain their the structure of the server (Fig.6). We observe that the described toy problem can easily performed in inexpensively way by means collection of distributed resources of ENEA-GRID technologies and middleware. Fig.1: An internal view of the Frascati Tokamak Upgrade class gradia- m gra class m Fig.2: The schematic representation of the twelve cameras of FTU. Fig.3: The figure represents the ER model: there are basic tables (CAMS, FOLDERS, IMAGES) and tables for each operation associated to an image. Example of Application description Fig.4: Class diagram. The table CAM is composed by several FOLDER each of which is a composition of IMAGE. Fig.6 Method HistogramImg(...) calculates histogram of image and save them in folder Histog_img which reproduces the structure: Cam/Folder/Image. The new path is: Histog_img/nomeCam/nomeFold/ hist_nomeimg (nomeimg is the name of input image). Method colortogray( ) converts an image into a gray-scale image and save it in the folder Gray_img which reproduces the structure Cam/Folder/Image. New path of image is Gray_img/nomeCam/nomeFold/gray_nomeImg References - The Definitive Guide to ImageMagick, Michael Still: Books - Digital Image Processing Using Matlab, Gonzalez - Thinking in C++, Bruce Eckel - Image analysis of a nuclear plasma: Frascati Tokamak Upgrade using IDL and ENEA-GRID technologies (poster) - M. Chinnici, S. Migliori, R. De Angelis, S. Borioni, S. Pierattini E-Science conference, Nsaples sp12_graf3d/

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