Fruit Classification through image processing

Project Title

Fruit Classification through image processing

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

Fruit grading is an important process for producers which affects the fruits quality evaluation and export market.The main focus of our work is obtaining the analysis of different fruit quality detection techniques.Export management in our fruit industry is lacking day by day due to lack of technologies.For this purpose, small prototype with better processor should be implement. Whereas the recognition of fruits in the natural environment becomes challenging due to the involvement of complex backgrounds. Automatic classification of fruits via computer vision is still a complicated task due to the various properties of many types of fruits. Fruit grading is an important process for producers which affects the fruits quality evaluation and export market. Although the grading and sorting can be done by the human, but it is slow, labor intensive and tedious. Hence, there is a need of an intelligent fruit grading system.

Project Objectives

The objective of fruit classification using image processing is to design an incremental model to recognize the fruits based on quality of the fruit by ignoring external features like environment, noise and background. Similarly, to identify best quality fruits is cumbersome task. Therefore, we come up with the system where fruit is detected under natural lighting conditions. This just focus the image of particular fruit and identify the fruit. To improve the fruit quality for export market on the basis of sorting or grading through using image processing.

Project Implementation Method

The objective of fruit classification using image processing is to design and implement an incremental model to recognize fruits based on quality of the fruit by ignoring external features like environment, noise etc. Therefore, we come up with the system where we use logistic regression for classifying fruits based on supervised classification.Using this system in the future, consumers will be able to choose quality fruits locally by the use of appropriate budget.

Regression analysis

It is the process of estimating the relationships among variables and predicting where a particular variable belongs to which class. Regression is basically a two-class classification method. It is classified into two main categories; linear and logistic regression.

Why logistic regression?

Logistic regression allows non-linear boundary model for a two-category classification unlike linear regression which works only when two classes can be separated by a linear line. Logistic regression is used to predict the categorical dependent variable with the help of independent variables. The output of logistic regression problem can be only between the 0 and 1. Logistic regression can be used where the probabilities between two classes is required.

Benefits of the Project

The quality detection is efficient, accurate and time saving.

A fruit classification system may be used to help a super market cashier to identify the fruit species and prices.

Grading improves product uniformity within a particular grade and serves as the basis for prices. Increases the market efficiency.

It helps in understanding the images in order to gather symbolic and numerical information.

Grading is sorting or categorization of fruits into different grades according to the size of shapes and volume of fruit.

Increasing producers’ as well as distributor’s profits.

Export management will be improved in industries.

Technical Details of Final Deliverable

S. No	Tasks	Status	Implementation	Testing	Training	Design	Development
1.	Pre-processing	Complete	Done	Done	Done	Done	Done
2.	Segmentation	Complete	Done	Done	Done	Done	Done
3.	Feature Extraction	complete	Done	Done	Done	Done	Done
4.	Fruit recognition	complete	Done	Done	Done	Done	Done
5.	Hardware	In progress	Done	In progress	Done	Done	In progress

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Final Deliverable of the Project HW/SW integrated systemCore Industry FoodOther Industries Agriculture , Manufacturing , Others Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Industry, Innovation and Infrastructure, Responsible Consumption and Production, Partnerships to achieve the GoalRequired Resources

Elapsed time in (days or weeks or month or quarter) since start of the project	Milestone	Deliverable
Month 1	Project Selection	Fruit Classification Through Image Processing.
Month 2	Methodology Selection	Logistic Regression Technique.
Month 3	Software Learning and Designing	1-Preprocessing 2-Feature extraction
Month 4	Software Implementation	3-Image segmentation 4-Recognition All these steps are implement through MATLAB.
Month 5	Hardware selection	Design hardware in AutoCAD for initial adjustment.
Month 6	Hardware Implementation	Buy required equipment for designing of prototype.
Month 7	Thesis Completion	In process
Month 8	Project Completion	We will deliver full hardware Prototype