FUZZY INTERFACE-BASED WEED DETECTION SYSTEM USING IMAGE PROCESSING TECHNIQUES FOR SMART AGRICULTURE

Abstract

Image processing in detecting weeds is a field that is newly emerging and fast-growing, which can be revolutionary in modern agriculture. The technology helps farmers to recognize and monitor weeds in order to apply specific and effective weed control services. This paper is on the development and implementation of an image-capturing and image-processing system and the design of fuzzy logic on a decision-making platform that determines the suitable dosage level of suitably applied pesticide, together with its application spot concerning agricultural lands.

The natural way of fertilizing in the early days of farming included the use of manure and compost from chickens, cows, and horses. Although these natural methods increased the productivity, now, to keep in line with the rising global food demand, advanced image processing processes are also used in addition to that.

We are using MATLAB as the background processing technique in the field images and identification of grassy weed areas in this work. The fuzzy logic system operates on weed coverage and patch values as well as the usage of membership functions of decision making, one of which involves settling on a rate of application of herbicides at particular areas within the field.

Due to the increase in global population and the exhaustion of natural resources, health-related and sustainable agricultural methods are becoming a focus. As depicted in this paper, the application of image processing technologies can be very crucial in curbing such challenges