Apple Grading Method Based on Features Fusion of Size, Shape

As grading results of apples based on the single feature such as size, shape or color are not accurate, this paper

proposes a multi-feature information fusion method based on BP neural network and D-S evidential theory to

improve the accuracy of apple grading. Firstly, size, shape and color features are extracted from the processed images

of apples. Secondly, apples are classified with each kind of feature by BP network classifier and as independent

evidences, the outputs of classifiers are combined to construct the basic probability assignment (BPA). Finally, using

D-S fusion rules of evidences to make the decision and achieve the final grading result. The experimental results have

shown that the decision information fusion method based on size, shape or color features has good performance on

accuracy compared to the single feature-based method in apple grading.

I want to implement whole work on matlab

Kemahiran: Reka Bentuk Grafik, Matlab and Mathematica, SEO

Lihat lagi: apples size grading, combined result, apple grading, apple i work, performance based, neural, neural network, method, matlab network, grading, fusion, color grading, apples, apple, work apple, matlab implement neural network, matlab basic, images matlab, probability assignment, features matlab, size color, accurate method, matlab based, theory assignment, information theory assignment

Tentang Majikan:
( 0 ulasan ) India

ID Projek: #1543611

2 pekerja bebas membida secara purata ₹2250 untuk pekerjaan ini


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