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dc.contributor.authorde Alwis, KCM
dc.contributor.authorUdayangi, TGI
dc.date.accessioned2023-06-28T04:57:07Z
dc.date.available2023-06-28T04:57:07Z
dc.date.issued2022
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/6434
dc.description.abstractCosmetic products are intended to enhance certain aspects that appeal to the aesthetic senses, particularly sight, such as the shape, color, or form of human beings. The global cosmetics market has shown consistent growth throughout time due to the consumers who are mindful of their appearance However, consumers encounter certain issues when using them. As a result of the research study's findings, it is evident that majority of the cosmetic product consumers face difficulties in understanding the meanings of the ingredients also some ingredient names are not correctly included in the product. The popular side effects faced by cosmetic consumers are Skin Rashes, Pimples, Dryness, and Irritation. This study is aimed at developing a web application to ensure the safety of the cosmetics products used by consumers in their day-to-day life. This proposed system will allow the user to assure safety by uploading an image of the ingredient label or by manually typing the lists of ingredients. Here, the subset of the image processing domain, Optical Character Recognition technology is used to extract text from the uploaded image. It will output a report by displaying the descriptions of each ingredient, respective severity scores, and the overall score of the product by mentioning whether it is favorable or harmful to the health. Here the necessary datasets are gathered from a reliable and accurate source. This system will ultimately contribute the economic growth and will increase the sales of products and the safety of the consumers in the beauty industryen_US
dc.language.isoenen_US
dc.subjectOptical Character Technologyen_US
dc.subjectCosmetic Productsen_US
dc.subjectSafety Assuranceen_US
dc.titleWellnessCare: OCR-based Web Application for Cosmetic Product Safety Assuranceen_US
dc.typeArticle Full Texten_US
dc.identifier.facultyComputingen_US
dc.identifier.journalKDU IRCen_US
dc.identifier.pgnos243-249en_US


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