Infected Fruit Part Detection using K-Means Clustering Segmentation Technique
نویسندگان
چکیده
منابع مشابه
Infected Fruit Part Detection using K-Means Clustering Segmentation Technique
— Nowadays, overseas commerce has increased drastically in many countries. Plenty fruits are imported from the other nations such as oranges, apples etc. Manual identification of defected fruit is very time consuming. This work presents a novel defect segmentation of fruits based on color features with K-means clustering unsupervised algorithm. We used color images of fruits for defect segmenta...
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Nowadays, overseas commerce has increased drastically in many countries. Plenty fruits are imported from the other nations. Manual identification of defected fruit is very time consuming. The proposed paper presents defect segmentation of fruits based on surface color features with unsupervised K-Means clustering and Fuzzy C-Means algorithms. As the first step, the digital color images of defec...
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ژورنال
عنوان ژورنال: International Journal of Interactive Multimedia and Artificial Intelligence
سال: 2013
ISSN: 1989-1660
DOI: 10.9781/ijimai.2013.229