Computer vision based analysis and detection of defects in fruits causes due to nutrients deficiency
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Computer vision based analysis and detection of defects in fruits causes due to nutrients deficiency Yogesh1 • Ashwani Kumar Dubey1 • Rajeev Ratan2 • Alvaro Rocha3 Received: 11 September 2019 / Revised: 25 November 2019 / Accepted: 8 December 2019 Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract Presently, the fruit industry requires a fast and efficient method for classification and recognition of the quality of fruits in bulk processing. Fruit recognition based on computer vision is quite challenging as it is based on the intensity, size, contour, and texture features extraction from fruits along with their suitable classifier selection. In this paper, the pixels containing the defected regions are segmented and their features are extracted. Further, a support vector machine (SVM) classifier is used to identify the defects and recognizes the cause with its stage. During the process of classification, fruits are categorized into two groups, defected and no-defect. The sample image observed defected further classified into three categories as the first, second and final stage of fruit defect. The sample testing at an early stage helps one to further proceed with the production or halt based on the outcome of a computer vision-based recognition system. Keywords Computer vision Fruits classification Image processing Recognition Segmentation
1 Introduction The increasing demand in the agriculture sector in terms of quality and quantity is fulfilled by the modernization of agriculture. Computer vision (CV) based technique discovers many applications in quality estimation and their classification in fruit industries. CV based system produces high-quality products compared to traditional human-based approach as the classification of fruits requires adequate & Ashwani Kumar Dubey [email protected] Yogesh [email protected] Rajeev Ratan [email protected] Alvaro Rocha [email protected] 1
Department of Electronics & Communication Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, Uttar Pradesh, India
2
Department of Electronics and Communication Engineering, MVN University, Palwal, Haryana, India
3
Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal
knowledge of a variety of fruits and their defects. The traditional approach requires skilled persons for quality inspection and their classification. A recent development in computer vision unlocks a broad field for new opportunities and its applications in fruit industries. Human involvement for quality measures affected by physical factors, therefore, considered as inconsistent. The classification response differs from person to person as a methodology based on feeling and seeing of fruits. A system with characteristics of classification of fruit along with their internal and external quality inspection system requires quick response and high precision level that also retains the international standards al
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