Juan Carlos Briceño

Learn More
The present work presents a biometric identification system for hand shape identification. The different contours have been coded based on angular descriptions forming a Markov chain descriptor. Discrete Hidden Markov Models (DHMM), each representing a target identification class, have been trained with such chains. Features have been calculated from a(More)
Earth's biodiversity has been suffering the effects of human contamination , and as a result there are many species of plants and animals that are dying. Automatic recognition of pollen species by means of computer vision helps to locate specific species and through this identification, study all the diseases and predators which affect this specie, so(More)
— Conserving earth's biodiversity for future generations is a fundamental global task, where automated recognition of pollen species by means of computer vision represents a highly prioritized issue. This work focuses on analysis and classification stages. The morphological details of the contour are proposed as pollen grains discriminative features. The(More)
This present work presents a robust system for the feature reduction, using Deoxyribonucleic Acid (DNA) primer. This system reaches up to 100% classes identification based on Support Vector Machines (SVM). In particular, the biochemical parameterization has 89 Random Amplified polymorphic DNA (RADP) primers of Pejibaye Palm races, and it has been reduced to(More)