The automatic identification and classification of musical genres based on the sound similarities to form musical textures, it is a very active investigation area. In this context it has been created recognition systems of musical genres, formed by time-frequency characteristics extraction methods and by classification methods. The selection of this methods are important for a good development in the recognition systems. In this article they are proposed the Mel-Frequency Cepstral Coefficients (MFCC) methods as a characteristic extractor and Support Vector Machines (SVM) as a classifier for our system. The stablished parameters of the MFCC method in the system by our time-frequency analysis, represents the gamma of Mexican culture musical genres in this article. For the precision of a classification system of musical genres it is necessary that the descriptors represent the correct spectrum of each gender; to achieve this we must realize a correct parametrization of the MFCC like the one we present in this article. With the system developed we get satisfactory detection results, where the least identification percentage of musical genres was 66.67% and the one with the most precision was 100%.
Biometrics refers to identify people through their physical characteristics or behavior such as fingerprints, face, DNA,
hand geometries, retina and iris patterns. Typically, the iris pattern is to acquire in short distance to recognize a person,
however, in the past few years is a challenge identify a person by its iris pattern at certain distance in non-cooperative
environments. This challenge comprises: 1) high quality iris image, 2) light variation, 3) blur reduction, 4) specular
reflections reduction, 5) the distance from the acquisition system to the user, and 6) standardize the iris size and the density
pixel of iris texture. The solution of the challenge will add robustness and enhance the iris recognition rates. For this
reason, we describe the technical issues that must be considered during iris acquisition. Some of these considerations are
the camera sensor, lens, the math analysis of depth of field (DOF) and field of view (FOV) for iris recognition. Finally,
based on this issues we present experiment that show the result of captures obtained with our camera at distance and
captures obtained with cameras in very short distance.
Current search engines are based upon search methods that involve the combination of words (text-based search); which
has been efficient until now. However, the Internet’s growing demand indicates that there’s more diversity on it with each
passing day. Text-based searches are becoming limited, as most of the information on the Internet can be found in different
types of content denominated multimedia content (images, audio files, video files).
Indeed, what needs to be improved in current search engines is: search content, and precision; as well as an accurate display
of expected search results by the user. Any search can be more precise if it uses more text parameters, but it doesn’t help
improve the content or speed of the search itself. One solution is to improve them through the characterization of the
content for the search in multimedia files. In this article, an analysis of the new generation multimedia search engines is
presented, focusing the needs according to new technologies.
Multimedia content has become a central part of the flow of information in our daily life. This reflects the necessity of
having multimedia search engines, as well as knowing the real tasks that it must comply. Through this analysis, it is shown
that there are not many search engines that can perform content searches. The area of research of multimedia search engines
of new generation is a multidisciplinary area that’s in constant growth, generating tools that satisfy the different needs of
new generation systems.