Fruit recognition using Statistical and Features extraction by PCA
نویسندگان
چکیده
Fruits are an integral part of human diet since they a vital source minerals, vitamins, fiber, and phytonutrients. rich in potassium, vitamin C yet low fat, sodium, calories. A high fruit can help us avoid diseases including cancer, diabetes, heart disease, others. Without professional dietitian guidance, method that quickly reveals how many calories or consuming be helpful maintaining health. The use image processing methods is expanding across all academic fields, food science agriculture. identification plant fruits the extraction their features first topics covered this essay because essential to goal results Principal Component Analysis (PCA) build accurate, efficient, reliable framework. Fruit detecting software could simplify labor. Based on color shape characteristics, several recognition have been developed. However, values photos comparable even same. As result, utilizing PCA feature analysis identify distinguish still not strong effective enough boost accuracy. In paper, algorithm based proposed. establishment database with 6 distinct categories 36 photographs second topic essay. study, classifier used implement system, proposed system's classification accuracy 75%.
 KEY WORDS: Fruit, recognition, Feature extraction, Classification, (PCA).
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ژورنال
عنوان ژورنال: Academic journal of Nawroz University
سال: 2023
ISSN: ['2520-789X']
DOI: https://doi.org/10.25007/ajnu.v12n3a1687