IPO Model Conceptual Framework of Herbal Identification App

IPO Model Conceptual Framework of Herbal Identification App

The capstone project entitled “Herbal Identification App using Image Processing” is a machine learning project using OpenCV and Python. The said application can be implemented in a web or mobile based platform.

Scope and Limitation

The aim of this study is to design and develop an application that could identify the name of the herbal plant based on the image captured. As of the moment, the application can only identify the plant based on the different pre-processing techniques used for feature extraction from a leaf. Herbal plants are the scope of this project but the algorithm and the output of the project could be implemented on other types of plants.

Conceptual Framework/Model

Conceptual Model of Herbal Identification App using Image Processing
Conceptual Model of Herbal Identification App using Image Processing

Figure 1.0 Conceptual Model of Herbal Identification App using Image Processing

The study is guided based on the Logic Model Approach to design, develop, implement and basis for identifying and measuring the impact of the utilization of Herbal Identification App using Image Processing.

Input

Brainstorming – this is the part where the researchers have talked what will be the capstone project of the group. Creative ideas were brought out and it was decided by the team to pursue a project related to machine learning. It was the selected topic since it a trending subject in the field of computing and programming.

Problem Identification – machine learning in general is a broad topic. Researchers have identified the list of possible innovation that could help the community using the machine learning concept. Herbal plant identification was the project sought by the researchers.

Literature Review – the researchers have conducted researches and studies that are closely related to the proposed system. This process will help the researchers in the development of the project or system.

Process

Development Tools

OpenCV – OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly aimed at real-time computer vision. (https://en.wikipedia.org/wiki/OpenCV)

Machine Learning – Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to do so. (https://en.wikipedia.org/wiki/Machine_learning)

Python – Python is an interpreted, high-level and general-purpose programming language. Python’s design philosophy emphasizes code readability with its notable use of significant indentation. (https://en.wikipedia.org/wiki/Python_%28programming_language%29)

Software Development Life Cycle

The researchers used Rapid Application Development or RAD as the software development life cycle.

Analysis and Quick DesignDuring Analysis and Quick Design phase, the researchers will conduct an interview with the experts in the field of herbal plants and medicines. After the conduct of data gathering, the researchers will make an initial design for the proposed system based on the information provided by the experts.

Data Analysis – The researchers will process and analyses the gathered data. The result of analysis will benefit the developed system to determine the solutions needed by the respondents.

System DesignIn this phase, the developer will start to develop the proposed system including the data sets.

Prototype CycleThis phase includes three stages, the building demonstration, and refinement. The researchers will build a prototype. After building the prototype, the researcher will demonstrate to the client the different functions, features and how the application works. The last phase is refinement; the researcher will refine the system, including the flow, needs or wants and functions based on their requirements.

Testing In this phase, the system will be brought for testing using the following methods.

Testing involves white box testing and black box testing.

  • White box testing. Is a software testing method in which the internal structure/ design/ implementation of the item being tested is known to the tester. White boxes are the IT Experts and developers who know how to test the system.
  • Black Box Testing. Is a software testing method in which the internal structure/ design/ implementation of the item being tested is NOT Known to the tester. After the above testing, results and recommendations will be recorded to further improve the system.

Implementation – This phase will discuss the implementation of the proposed system, if the recommendation and wants of respondents were met.

Output

Deployment and Implementation of Herbal Identification App using Image Processing is available for both mobile and web platforms. The output is an innovation that could easily identify herbal plant based on the image captured (leaf). It is a comparison technique using several methods. The project will match the captured image to the existing data sets. Application would then suggest herbal plant based on the available resources. The proposed application is far from perfect and the more data it collects the higher the percentage it could predict and identify.

Outcome

  • Archiving of herbal plants is very helpful
  • Identification of herbal plants and its purpose is very easy and accessible

Impact

Community awareness on the benefits of the herbal plants

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