@conference {Carbonaro1999241,
	title = {A comprehensive approach to image-contrast enhancement},
	booktitle = {Proceedings - International Conference on Image Analysis and Processing, ICIAP 1999},
	year = {1999},
	note = {cited By 3},
	pages = {241-246},
	abstract = {The paper describes a novel comprehensive approach to image-contrast enhancement in the spatial domain. Instead of defining another transformation function our strategy consists of adopting a general functional form, able to map different transformation functions, and in using a learning technique to select the parameter values that are optimal for the image being processed. First, local measures of spatial activity are assigned to each pixel of the image. Second, the local contrast value for each pixel is computed according to a function which is based on human visual response. Third, the parameters of a comprehensive contrast-enhancement function are selected by a genetic algorithm on the basis of the spatial activity of the image resulting from the transformation. The validity of the proposed technique is confirmed both perceptually, that is, higher fitness values correspond to the images that have been judged better by human observers, and by comparative evaluations of our algorithm with respect to classical methods. {\textcopyright} 1999 IEEE.},
	doi = {10.1109/ICIAP.1999.797602},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77956062070\&partnerID=40\&md5=bec0356d2a98fdaca54e11dd4711add0},
	author = {A. Carbonaro and Primo Zingaretti}
}
@article {Zingaretti1998177,
	title = {Route following based on adaptive visual landmark matching},
	journal = {Robotics and Autonomous Systems},
	volume = {25},
	number = {3-4},
	year = {1998},
	note = {cited By 3},
	pages = {177-184},
	abstract = {Route following based on visual landmark matching may require many models to cover all different situations. This paper describes a system that is able to adapt template{\textquoteright}s modelling parameters to environmental conditions (lighting, shadows, etc.) by a genetic learning technique. In addition, the mobile robot self-localisation is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence problem in the 3D position estimation. The experimental results show that the tracking robustness is improved, while using a small set of templates. {\textcopyright} 1998 Elsevier Science B.V. All rights reserved.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0032208707\&partnerID=40\&md5=8655435896f671afeeb70009f9086bee},
	author = {Primo Zingaretti and A. Carbonaro}
}
@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 {Carbonaro1997147,
	title = {Landmark matching in a varying environment},
	booktitle = {Proceedings of the Euromicro Workshop on Advanced Mobile Robots, EUROBOT},
	year = {1997},
	note = {cited By 4},
	pages = {147-153},
	abstract = {A system for landmark tracking by a template matching approach is described. Route following based on landmarks may require many models to cover all different situations, so a genetic algorithm learning technique is used to adapt modelling parameters to environmental conditions (lighting, shadows, reflexes, etc.) during the tracking. In addition, the mobile robot self-localization is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence analysis in the 3-D position estimation. The experimental results show that the tracking robustness is improved when the adaptive template matching is used for landmark tracking.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0031356261\&partnerID=40\&md5=84da6f7845bf77d41951a6da2296155c},
	author = {A. Carbonaro and Primo Zingaretti}
}
@conference {Carbonaro1997229,
	title = {Object tracking in a varying environment},
	booktitle = {IEE Conference Publication},
	number = {443 pt 1},
	year = {1997},
	note = {cited By 3},
	pages = {229-233},
	abstract = {An object tracking system based on a template matching approach is demonstrated. The system identifies the target and tracks a sequence of video-recorded images without losing the object by using a genetic algorithm (GA)-based learning to adapt template matching processes to environmental conditions. The adaptive GA generates templates better than fixed, random or indexed template generation techniques in terms of both the cross-correlation score and time necessary to choose the template model. While the overload using the GA is minimal if it is not necessary to change template model, in all other cases the GA offers a better solution to the search the associated search and optimization problem than usual algorithms.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0031337379\&partnerID=40\&md5=91c558ca9bbaca4384ce4e7619dd71f4},
	author = {A. Carbonaro and Primo Zingaretti}
}
