Semantic Driven Automated Image Processing Using the Concept of Colorimetry

Color is the visual perceptual property of humans. Color obtains from the band spectrum light-weight {of sunshine} (dissemination of wavelength versus light energy) interacting within the eye with the spectral band sensitivities of the sunshine receptors. Color classification and actual descriptions of color are also connected with objects, materials, light-weight sources, etc., supported their physical properties like light-weight absorption, reflection, or emission spectra. Colorimetry (quantitative chemical analysis) is that the science and psychophysical aspects of color that describes colorise numbers or provides a physical color match employing a kind of measuring instruments. Ontologies can be used and designed to reproduce dispense knowledge and control the semantic heterogeneity among color domains. Knowledge is collected by ability of individuals and represented in description logics. Thus ontology is a key implementation strategy of semantic research, which provides knowledge footprint of the corresponding domain. This paper presents ontology for using various color categories. The resulting ontology can be used by human or machine to extract the relevant prominent features from different color categories to find out the inter-connection among physical aspects of color model and therefore the physiological aspects of human vision. This paper is basically an approach to automate the digital image processing method using the concept of colorimetry and semantics. This paper focused on the development of semantic information which represents the color domains of the image resolution pixel value. The aim of this ontology is to modify machines to create and perceive visual color description schemes and descriptors that are expressed in web ontology language (OWL) format.