@conference {Montesanto2007229,
	title = {Fingerprints recognition using minutiae extraction: A fuzzy approach},
	booktitle = {Proceedings - 14th International conference on Image Analysis and Processing, ICIAP 2007},
	year = {2007},
	note = {cited By 0},
	pages = {229-234},
	abstract = {The aim of this paper is to study the fingerprint verification based on local ridge discontinuities features (minutiae) only using grey scale images. We extract minutiae using two algorithms those following ridge lines and then recording ridge endings and bifurcations. Moreover we use a third algorithm able to develop a minutiae verification processing a local area using a neural network ( multilayer perceptron). Fingerprint distortion is filtered using a minutiae whole representation based on regular invariant moments. The results of the three minutiae extraction algorithms are joined during the minutiae pattern matching phase for fingerprint verification. Here we propose a new method of matching that use fuzzy operator to bypass the problem of different numbers of minutiae extracted from the algorithms. Experimental evidences show fingerprint recognition up to 95\%. {\textcopyright} 2007 IEEE.},
	doi = {10.1109/ICIAP.2007.4362784},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-48149113403\&partnerID=40\&md5=01f07886247083f3db66c7477c334984},
	author = {A. Montesanto and Paola Baldassarri and Vallesi, G. and Guido Tascini}
}
@article {Montesanto200684,
	title = {Navigation with memory in a partially observable environment},
	journal = {Robotics and Autonomous Systems},
	volume = {54},
	number = {1},
	year = {2006},
	note = {cited By 3},
	pages = {84-94},
	abstract = {The paper presents an architecture that allows the reactive visual navigation via an unsupervised reinforcement learning. This objective is reached using Q-learning and a hierarchical approach to the developed architecture. Using these techniques requires a deviation from the Partially Observable Markov Decision Processes (POMDP) and some innovations: heuristic techniques for generalizing the experience and for treating the partial observability; a technique for the speed adjournment of the Q function; the definition of a special reinforcement policy adequate for learning a complex task without supervision. The result is a satisfactory learning of the navigation assignment in a simulated environment. {\textcopyright} 2005 Elsevier B.V. All rights reserved.},
	doi = {10.1016/j.robot.2005.09.015},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-29344460057\&partnerID=40\&md5=a3f0d1229db6d5c8658cd509ca5acf81},
	author = {A. Montesanto and Guido Tascini and Paolo Puliti and Paola Baldassarri}
}
@article {Baldassarri2003201,
	title = {Self-organizing maps versus growing neural gas in a robotic application},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {2687},
	year = {2003},
	note = {cited By 1},
	pages = {201-208},
	abstract = {The paper proposes a method for visual based self-localisation of a mobile agent in indoor environment. The images acquired by the camera constitute an implicit topological representation of the environment. The environment is a priori unknown and so the implemented architecture is entirely unsupervised. To compare the performance of some self-organising neural networks, a similar neural network architecture of both Self-Organizing Map (SOM) and Growing Neural Gas (GNG) has been realized. Extensive simulations are provided to characterise the effectiveness of the GNG model in recognition speed, classification tasks and in particular topology preserving as compared to the SOM model. This behaviour depends on the following fact: a network (GNG) that adds nodes into map space can approximate the input space more accurately than a network with a predefined structure and size (SOM). The work shows that the GNG network is able to correctly reconstruct the environment topological map. {\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-35248829969\&partnerID=40\&md5=28fe2f7301103d80e28ff664c2a74906},
	author = {Paola Baldassarri and Paolo Puliti and A. Montesanto and Guido Tascini}
}
@conference {Baldassarri2003368,
	title = {Visual self-localisation using automatic topology construction},
	booktitle = {Proceedings - 12th International Conference on Image Analysis and Processing, ICIAP 2003},
	year = {2003},
	note = {cited By 0},
	pages = {368-374},
	abstract = {The paper proposes a machine learning method for self-localising a mobile agent, using the images supplied by a single omni-directional camera. The images acquired by the camera may be viewed as an implicit topological representation of the environment. The environment is a priori unknown and the topological representation is derived by unsupervised neural network architecture. The architecture includes a self-organising neural network, and is constituted by a growing neural gas, which is well known for its topology preserving quality. The growth depends on the topology that is not a priori defined, and on the need of discovering it, by the neural network, during the learning. The implemented system is able to recognise correctly the input frames and to reconstruct a topological map of the environment. Each node of the neural network identifies a single zone of the environment and the connections between the nodes correspond to the real space connections in the environment. {\textcopyright} 2003 IEEE.},
	doi = {10.1109/ICIAP.2003.1234077},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84890545853\&partnerID=40\&md5=6954a4c9b47cdb3e275eac96afdf95a2},
	author = {Paola Baldassarri and Paolo Puliti and A. Montesanto and Guido Tascini}
}
@conference {Tascini1998278,
	title = {Unauthorized access identification in restricted areas},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {3364},
	year = {1998},
	note = {cited By 0},
	pages = {278-286},
	abstract = {The paper describes a system to control vehicle accesses in restricted areas. The signalling of vehicles whose license- plates do not belong to a specific database is the aim of the system. The adaptation to different environmental conditions, and the identification of a vehicle by processing the license- plate pattern as a whole, without considering the recognition of the characters, are its two main characteristics. The system implements a recognition engine constituted by two modules. First, the system analyzes the video-recorded sequences to select a frame in which the license-plate satisfies pre-defined constraints, and extracts the license- plate template on which the matching with the model templates stored in the database will be performed. Second, vehicle identification is performed by a genetic template matching that, without requiring a high computational complexity, provides adaptation to normal environmental variations by exploiting learning capabilities. The implemented system, forced to distinguish only between authorized and unauthorized vehicles according to a threshold in the genetic fitness function, shows robust performance on Italian cars, but it is adaptable to different license-plate models, and is independent from outdoor conditions. {\textcopyright}2003 Copyright SPIE - The International Society for Optical Engineering.},
	doi = {10.1117/12.317481},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-62249155465\&partnerID=40\&md5=c5bfb42de0062e33b5145339e0517adb},
	author = {Guido Tascini and A. Carbonaro and Primo Zingaretti}
}
@conference {Conte19961213,
	title = {Automatic analysis of visual data in submarine pipeline inspection},
	booktitle = {Oceans Conference Record (IEEE)},
	volume = {3},
	year = {1996},
	note = {cited By 8},
	pages = {1213-1219},
	abstract = {An automatic system for analysis and interpretation of visual data from submarine pipeline inspection operates using images collected by cameras mounted on an unmanned Remotely Operated Vehicle (ROV) that moves along the pipeline. The system supports the operator in navigating the ROV and in detecting structural elements of the pipeline such as anodes, gravel heaps and reference bands. The system employs a feature based technique for recognizing the pipeline{\textquoteright}s profile and for detecting the structural elements. Information gathered by analyzing and interpreting the visual data can be used for automatic guidance and inspection by integrating the system into a larger architecture.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0030385353\&partnerID=40\&md5=d5723a92ebcff100f3868adc25135935},
	author = {Conte, G. and S.M. Zanoli and Perdon, A.M. and Guido Tascini and Primo Zingaretti}
}
@conference {Zingaretti1996129,
	title = {Imaging approach to real-time tracking of submarine pipeline},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {2661},
	year = {1996},
	note = {cited By 10},
	pages = {129-137},
	abstract = {The work presents a real-time underwater imaging system for identification and tracking of a submarine pipeline on a sequence of recorded images. The main novelty of this work relies on adopting an automatic approach that is entirely based on the analysis and interpretation of visual data, in spite of the various limitations upon the ability to image underwater objects. The analysis of the data is performed starting from image processing operations (like filtering, profile analysis, feature enhancement) implemented on a dedicated board. Then, the system employs an efficient dynamic process for recognizing the two contours of the pipeline. In each frame the system is able to determine the equations of the two straight lines corresponding to the pipeline contours. The system reaches satisfactory performances in real time operation: up to eight frames per second on a Pentium based PC. The results of this work are somewhat more meaningful as the input images were acquired by three cameras, mounted on a remotely operated vehicle travelling at one nautical mile an hour, without any attention either to illumination conditions or stability of cameras. This work is originated from the interest of Snamprogetti in enhancing the level of automation in submarine pipeline inspection.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0029754848\&partnerID=40\&md5=65001780f0cb94776ceeb1da3a6eec40},
	author = {Primo Zingaretti and Guido Tascini and Paolo Puliti and S.M. Zanoli}
}
@article {Tascini1996432,
	title = {Real-time inspection by submarine images},
	journal = {Journal of Electronic Imaging},
	volume = {5},
	number = {4},
	year = {1996},
	note = {cited By 5},
	pages = {432-442},
	abstract = {A real-time application of computer vision concerning tracking and inspection of a submarine pipeline is described. The objective is to develop automatic procedures for supporting human operators in the real-time analysis of images acquired by means of cameras mounted on underwater remotely operated vehicles (ROV). Implementation of such procedures gives rise to a human-machine system for underwater pipeline inspection that can automatically detect and signal the presence of the pipe, of its structural or accessory elements, and of dangerous or alien objects in its neighborhood. The possibility of modifying the image acquisition rate in the simulations performed on video-recorded images is used to prove that the system performs all necessary processing with an acceptable robustness working in real-time up to a speed of about 2.5 kn, widely greater than that the actual ROVs and the security features allow. {\textcopyright} 1996 SPIE and IS\&T.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0009091679\&partnerID=40\&md5=0be09172d776524c453eb82b24820faf},
	author = {Guido Tascini and Primo Zingaretti and Conte, G.}
}
@conference {Tascini199518,
	title = {Model attraction in medical image object recognition},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {2436},
	year = {1995},
	note = {cited By 0},
	pages = {18-29},
	abstract = {This paper presents as new approach to image recognition based on a general attraction principle. A cognitive recognition is governed by a {\textquoteright}focus on attention{\textquoteright} process that concentrates on the visual data subset of task- relevant type only. Our model-based approach combines it with another process, focus on attraction, which concentrates on the transformations of visual data having relevance for the matching. The recognition process is characterized by an intentional evolution of the visual data. This chain of image transformations is viewed as driven by an attraction field that attempts to reduce the distance between the image-point and the model-point in the feature space. The field sources are determined during a learning phase, by supplying the system with a training set. The paper describes a medical interpretation case in the feature space, concerning human skin lesions. The samples of the training set, supplied by the dermatologists, allow the system to learn models of lesions in terms of features such as hue factor, asymmetry factor, and asperity factor. The comparison of the visual data with the model derives the trend of image transformations, allowing a better definition of the given image and its classification. The algorithms are implemented in C language on a PC equipped with Matrox Image Series IM-1280 acquisition and processing boards. The work is now in progress.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0029452584\&partnerID=40\&md5=181cb1d8753867d28066421ab8229a59},
	author = {Guido Tascini and Primo Zingaretti}
}
@conference {Tascini19942378,
	title = {Attraction based recognition},
	booktitle = {Proceedings of the IEEE International Conference on Systems, Man and Cybernetics},
	volume = {3},
	year = {1994},
	note = {cited By 0},
	pages = {2378-2383},
	abstract = {An approach to image recognition is proposed, which is achieved through the correspondences between predicted and measured properties: points, lines, regions, color, shape, etc. Image parts are subjected to a series of transformations performed by the recognition process. In these transformations, called image chaining, there is a grouping of image parts or features due to a field continually perturbed by the recognition process. A fundamental role is played by the spatial correspondences together with an intentional behavior of the transformed visual data called attraction. After a definition of the attraction principle, the paper describes the attraction process, and justifies the image chaining concept. Finally, a series of processes - segmentation refinement, search space reduction, and perceptual organization - are interpreted in terms of the attraction principle.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0028742684\&partnerID=40\&md5=9925689ed71ffc413fb731f2205f4173},
	author = {Guido Tascini and Primo Zingaretti}
}
@conference {Tascini19941722,
	title = {Automatic quantitative analysis of lumbar bone radiographs},
	booktitle = {IEEE Nuclear Science Symposium \& Medical Imaging Conference},
	number = {pt 3},
	year = {1994},
	note = {cited By 1},
	pages = {1722-1726},
	abstract = {In the current radiological diagnosis the radiographs often appear as {\textquoteleft}rough{\textquoteright} means to be understood due to the bad quality of radiographic images. The aim of the work is to guarantee a diagnostic support even in presence of radiographic means only, with a little cost increment due to a computer system, by supplying a useful primary screening tool that automatically analyzes digitized radiographs and gives important features relevant from medical standpoint. The specific domain of image analysis concerns the osteoporosis which is a long term diseases requiring an accurate measurement of bone density and a periodic follow-up. The automatic image processing method described in the work goes through a series of steps: selection of the region of interest, first preprocessing, extraction of the vertebral left side, second preprocessing, extraction of upper and lower borders of the end plates, detection of the greatest uniform area inside the vertebral body, third preprocessing, correction of image disuniformity, detection of the end plates, feature detection (variance, mean-gray, concavity, body and tissue density, etc.). The automation of the process is complete and the results good agree with those obtained from human analysis.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0028277067\&partnerID=40\&md5=7871b50c44eb8cbdb7e70759b9b2eb0d},
	author = {Guido Tascini and Primo Zingaretti}
}
@conference {Tascini1994838,
	title = {Image sequence recognition},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {2308},
	number = {p 2},
	year = {1994},
	note = {cited By 1},
	pages = {838-847},
	abstract = {Image sequence recognition is a problem that occurs in computer vision and particularly in mobile robot vision. The feature based method has been selected to solve this problem. The method first extracts the features as corners, points of curvature, lines etc. Then the correspondence of these features is established between two successive frames, and finally motion parameters and object structure from correspondences are computed. Test results demonstrating the method are included.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0028735739\&partnerID=40\&md5=2752672a7fe70d15fb9df66474f82faf},
	author = {Guido Tascini and Primo Zingaretti}
}
@conference {Tascini1993126,
	title = {Handwritten character recognition using background analysis},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {1906},
	year = {1993},
	note = {cited By 0},
	pages = {126-133},
	abstract = {The paper describes a low-cost handwritten character recognizer. It is constituted by three modules: the {\textquoteleft}acquisition{\textquoteright} module, the {\textquoteleft}binarization{\textquoteright} module, and the {\textquoteleft}core{\textquoteright} module. The core module can be logically partitioned into six steps: character dilation, character circumscription, region and {\textquoteleft}profile{\textquoteright} analysis, {\textquoteleft}cut{\textquoteright} analysis, decision tree descent, and result validation. Firstly, it reduces the resolution of the binarized regions and detects the minimum rectangle (MR) which encloses the character; the MR partitions the background into regions that surround the character or are enclosed by it, and allows it to define features as {\textquoteleft}profiles{\textquoteright} and {\textquoteleft}cuts;{\textquoteright} a {\textquoteleft}profile{\textquoteright} is the set of vertical or horizontal minimum distances between a side of the MR and the character itself; a {\textquoteleft}cut{\textquoteright} is a vertical or horizontal image segment delimited by the MR. Then, the core module classifies the character by descending along the decision tree on the basis of the analysis of regions around the character, in particular of the {\textquoteleft}profiles{\textquoteright} and {\textquoteleft}cuts,{\textquoteright} and without using context information. Finally, it recognizes the character or reactivates the core module by analyzing validation test results. The recognizer is largely insensible to character discontinuity and is able to detect Arabic numerals and English alphabet capital letters. The recognition rate of a 32 {\texttimes} 32 pixel character is of about 97\% after the first iteration, and of over 98\% after the second iteration.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0027277522\&partnerID=40\&md5=06fd7da850b665db5896240114bab4e7},
	author = {Guido Tascini and Paolo Puliti and Primo Zingaretti}
}
@conference {Tascini1993322,
	title = {Retina vascular network recognition},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {1898},
	year = {1993},
	note = {cited By 5},
	pages = {322-329},
	abstract = {The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0027873308\&partnerID=40\&md5=fe51e921b3d6ecbbbd0483a977269acd},
	author = {Guido Tascini and Passerini, G. and Paolo Puliti and Primo Zingaretti}
}
@conference {Tascini1991178,
	title = {Decision support system for capillaroscopic images},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {1450},
	year = {1991},
	note = {cited By 1},
	pages = {178-185},
	abstract = {The aim of the paper is to describe a decision support system operating in the area of capillaroscopic images. The system automatically sites the capillaroscopic analyzed image into one of the following classes: normal, diabetic and sclerodermic. The automatic morphometric analysis attempts to imitate physician behaviour and requires the introduction of some particular features connected with the specific domain. These features allow achieving a symbolic representation of the capillary partitioning it into three components: apex, arteriolar and venular side. The system is hierarchically organized in two levels. The system has been successfully used for obtaining images of nailfold capillaries of human finger.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0025798390\&partnerID=40\&md5=05b1aa9225d95f1ed2cecdc0a5268c2a},
	author = {Guido Tascini and Paolo Puliti and Primo Zingaretti}
}
@article {Palareti1988307,
	title = {Prolong approach to image segmentation},
	journal = {Applied Artificial Intelligence},
	volume = {2},
	number = {3-4},
	year = {1988},
	note = {cited By 0},
	pages = {307-331},
	abstract = {Segmentation is a problem in computer vision. It attempts to supply primitives for higher-level processes of interpretation. A multithreshold approach has already given acceptable results. This paper presents a Prolog implementation of a multithreshold system. The algorithms implemented concern image representation, connected regions, identification, and contour detection. The improvement of algorithms in a logic language rather than in a procedural one appeared to be of particular interest. The main reasons for this are implementation facility and the natural use of logic programming in the field of knowledge-based systems. In fact, a knowledge-based approach seems a reasonable solution to problems of assisted image understanding processes.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0024019798\&partnerID=40\&md5=bbf1d6d0aad82eee5540c0841df3bfad},
	author = {Palareti, Aldopaolo and Paolo Puliti and Guido Tascini and Primo Zingaretti}
}
