Page 550 - e-Book

4.1Vegetable quality digital image processing technique

Agriculture is backbone of our country. As a farming country we need produce and transfer

the vegetables. Manual sorting requires labors and it is time consuming. We need to identify
the vegetables (or) agriculture products without damaging it. So we propose a vegetable

recognition algorithm to recognize the vegetables with the help of digital image processing

technique. Digital images are profoundly successful in passing on specific feature that
assistance in specific assessments. In food science the way toward distinguishing the defect in

a vegetable acts an essential job. Vegetables production faces important losses in India due to

bacterial infection. Vegetable quality is usually mentioned size of vegetable, its shape, its
color and bruises from which it are often classified. The detection of diseases at time is that

the basis for management of a ranch. Many research papers have proposed many machine
vision strategies for recognizing vegetable deformities, as distinguishing defects in vegetables

at an early time can help decrease extra disease spreading to different parts of the vegetables
which will support the farming business. Bacterial illnesses of vegetables are most extreme

and unhelpful infections impacting in field crops. Under most conditions they can cause

confined pandemics impacting young rising vegetable. The exact detection of vegetable
illness is request undertaking task to specialists. This work presents vegetable disease

detection using image processing techniques to monitor diseases dependent on colour space
division. The datasets utilized for this analysis was gathered dependent on real sample images

for vegetable at various diseases, which were gathered from a market. The proposed approach
comprises of three unique stages; like pre-processing, segmentation, and classification. In the

pre-processing stage the pictures are resized to 250x250 pixels for decrease their shading

index. Contrast enhancement is utilized to improve the shading edges. In the segmentation
stage clustering algorithm is utilized to segment unnatural part of the vegetable images from

the original image. Extract the features of the image. The vegetables contain the features such

as color, shape, size, texture. By extracting these features, we can classify the vegetables. At
classification phase, Support Vector Machine is used to perform supervised Learning.

Finally, the name of the infected disease image is determined.
Conclusion:-

Agricultural productivity is very dependent on the economy. Plant diseases play an important
role in agriculture because plant diseases are very natural and failure to care will have serious

consequences for plants and therefore affect the quality, quantity, or productivity of the

product. Timely and accurate diagnosis of leaf diseases plays a major part in preventing loss

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