CLASSIFICATION OF NUT TYPES BASED ON SHAPE AND TEXTURE USING K-MEANS CLUSTERING
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Abstract
Nuts is component important in food man who gives nutrition and protein. Identification type peanut based on characteristic his physique can help in the sorting and processing process. In research this, we propose method For classify type nuts based on feature shape and texture use K-Means Clustering algorithm. Image data peanut collected and relevant features extracted. Through implementation of K-Means, we cluster nuts to in cluster based on similarity feature. Experimental results show that approach This own potency application practical in industry agriculture and processing food, as well capable identify pattern characteristics in characteristic physique nuts. This result open road for use analysis image and technique grouping in increase efficiency in production food and agriculture
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