A NEW IMAGE PROCESSING METHOD FOR IMPLEMENTATION OF WEED DETECTION
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Abstract
The earliest essential method of human subsistence on Earth was agriculture. Weeds are one of the most crucial elements, and in the agricultural sector, weed classification and identification are crucial from a scientific and economical standpoint. In the past, weeds were still identified by physical force in the majority of the planet. Subsequently, several automated methods for weed detection emerged, although they were not very accurate. The most important agricultural technique for increasing crop output and lowering herbicide application costs is weed control. The limitations of current weed detection systems prevent them from producing improved outcomes. This study shows how effective an image-processing technique is for identifying weeds in crops. when it is possible to identify the weeds in the unordered harvest in addition to those that are present collectively. Additionally, by recognizing the weed in recorded video as well as by identifying proof of weed in crop with an image, we can identify the weed and guarantee that it is there in the harvest. When weeds are managed, farming can be kept current by supplying crucial and basic protocols in horticultural frameworks for the future and by distributing inputs precisely where they are required. It offers quick and simple ways to identify and manage weeds.
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