Notice of Violation of IEEE Publication Principles: An assessment of MPEG-7 visual descriptors for images of maize plagues and diseases

Abstract

Notice of Violation of IEEE Publication Principles <br><br>“An Assessment of MPEG-7 Visual Descriptors for Images of Maize Plagues and Diseases” <br> by J. Manjarrez-Sanchez <br> in the IEEE Latin America Transactions, Vol. 18, No. 8, August 2020 <br><br> After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. <br><br> This paper contains significant portions of original content from the paper cited below. The original content was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. <br><br> “Análisis de descriptores visuales MPEG-7 para enfermedades y plagas en plantas de maíz” <br> by Luis Angel Pinedo Sánchez <br> in his Bachelor’s Thesis, Instituto Technologico Superior de Jerez <br><br> <br/> Feature description is a fundamental process in the analysis of images for content-based retrieval and classification, among other tasks in which the image feature descriptor should have enough discriminative power to differentiate similar from dissimilar images according with a distance measure. Although several descriptors have been proposed for a variety of images, the challenge is their suitability to solve these tasks efficiently. One proposal is the set of standard MPEG-7 visual descriptors. We address their suitability to efficiently describe plagues and diseases in images of maize plants. The importance of this crop is its worldwide relevance for human and animal consumption. Experiments for similarity search queries using a set of distance measures, show that the Color Structure Descriptor with the Bray-Curtis distance is the most efficient and provides around 68% precision in most cases.