Francisco Javier Gallegos-Funes

By Francisco J. Gallegos-Funes, Jose M. de-la-Rosa-Vazquez, Alberto J. Rosales-Silva and Suren Stolik Isakina

Part of the book: Ultrasound Imaging

By Alberto Rosales Silva, Angel Xeque-Morales, L.A. Morales -Hernandez and Francisco Gallegos Funes

Part of the book: Machine Vision

By Blanca E. Carvajal-Gámez, Francisco J. Gallegos-Funes, Alberto J. Rosales-Silva and Rene Santiago-Cruz

Part of the book: Recent Advances in Steganography

By Diana Alejandra Contreras Alejo and Francisco Javier Gallegos Funes

The content of this work is the proposal of the technical HS-ab for the detection and tracking of the regions of skin in real time. First, two proposed techniques are analyzed for the modeling of skin color in images using a combination of color spaces HSV with YCbCr and HSV with CIELab. In the process of definition of the intervals of pixels is taken into account the following: non-skin color uses the components H and S, whereas skin color uses the components Cb, Cr, a, and b. The results showed that the HS-ab technique is better than the HS-CbCr technique because of the precision in detecting skin color according to the percentages C (34.8%) and CDR (67%). After, the morphologic operations are applied to debug the images of the previous segmentation and detect regions of skin using methods such as blob extraction and contour detection. Subsequently, the tracking of skin color consists of calculating the moments and positions of each frame to know the trajectory of the regions of skin. The purpose of the work is to design an easy-to-use computer vision system that will facilitate the early rehabilitation of patients before they are clinically ready to be fitted with a prosthesis.

Part of the book: Biomimetic Prosthetics

By Miguel Ángel Castillo-Martínez, Francisco Javier Gallegos-Funes, Blanca E. Carvajal-Gámez, Guillermo Urriolagoitia-Sosa and Alberto J. Rosales-Silva

There are challenges in the image-based research to obtain information from the objects in the scene. Moreover, an image is a set of data points that can be processed as an object in similarity way. In addition, the research fields can be merged to generate a method for information extraction and pixel classification. A complete method is proposed to extract information from the data and generate a classification model capable to isolate those pixels that are plant from others are not. Some quantitative and qualitative results are shown to compare methods to extract information and create the best model. Classical and threshold-based state-of-art methods are grouped in the present work for reference and application in image segmentation, obtaining acceptable results in the plant isolation.

Part of the book: Information Extraction and Object Tracking in Digital Video