Mamdami Fuzzy Inference System

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The Mamdani Fuzzy Inference System is a method of reasoning based on fuzzy set theory, designed to model complex systems by mimicking human decision-making. It uses fuzzy rules and membership functions to process inputs and produce outputs, facilitating the handling of uncertainty and imprecision in data.

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Grading of Carabao Mango Using Image Processing

by SDIWC Organization

Grading the Quality of the mango is usuallyhandled physically which might not beaccurate due to the judgement of a person. Inthis study, image processing using MATLABis proposed using MandamiFuzzyInterference System. The Mango is placed... more

From the collected image, the computer program will collect the height and diameter of the sample mango by the use of boundary tracing. From the traced boundary, the program will measure the distance between one boundary to the other and gather the largest X and Y distance for the height and diameter respectively.

Figure 2. Spot Detection using Regionprops function The maturity will be based on the red means of the sample object. As the target colours are Green and Yellow, the only value that varies is the Red pixel values as a high red pixel value, a high green pixel value and a low pixel value produces a yellow colour and a low red pixel value, a high green pixel value and a low pixel value produces a green colour. The program will start by segmenting the colour between the mango and the background before collecting the

Figure 4.Membership function of Height variable

Figure 5. Membership function of Spot variable

A sample mango (Fig 8) which was 12 cm. tall was used to scale the distance between pixels as well as to check the limit of the height of the mango in pixels. From this mango sample, a 533 px tall mango is produced. Calculating for the limits of the acceptable height of an exportable mango, the for the lowest acceptable height of the mango, which is 10.5 cm, is scaled to 466 px; the highest acceptable height of the mango, which is 14 cm, is scaled to 622 px. Figure 8. An unripe mango and a ripe mango.

Figure 6.Membership function of Maturity variable There are five rules in the Fuzzy Inference system

Table 1 Input of the samples and the output from the Fuzzy Inference System The results show that the program is accurate enough to grade the mango. The system is strict enough to reject the sample mango if it is too large, is too small, is yellow or is blemished. While the system is more lenient on the grading between the spot detection considering our reference shows that there must be 0% tolerance in the spot detection of the system, it still show that the system may not be perfect as the REFERENCES

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