The dependency of technology on Digital Image Processing (DIP) and Artificial Intelligence (AI) is not new but more recently, AI emerges to be the essential component not only related to science and technology but in every field that human life touches or depends. The core concept of our proj
Dental Cavity Detection
The dependency of technology on Digital Image Processing (DIP) and Artificial Intelligence (AI) is not new but more recently, AI emerges to be the essential component not only related to science and technology but in every field that human life touches or depends.
The core concept of our project is to develop a system to aid dentists to determine the dental cavity, if occurs, by processing the dental X-Ray image of human jaw to highlight the essential features and send it to the developed AI engine to determine the position of the cavity.
The major advantages of our developed system are to ease the burden of manual processing of cavity determination and also it is not intrusive for patients having such cavities.
In this project, dental image X-Ray is analyzed using image processing and AI techniques and detect the cavity, if present, in the image.
Following are the key objectives of the project:
To develop an image processing module that processes the dental X-Ray image and as output effectively highlight the features of the human jaw so that essential feature points may be extracted for further analysis.
To develop an AI based machine learning module that is used to train the extracted feature points from the dental X-Ray image. A large set of these feature points are used for enhanced learning of the system.
To integrate these modules into a single system so that any dental X-Ray image of the jaw can be given as input, processed and provides the essential information about the presence and location of the cavity, if any.
This is a Research based project, and the main objective of this project is to implement the concepts of Digital Image Processing and Machine Learning in the field of dentistry and medical science.

In the project, the system is installed on Raspberry Pi using Python and OpenCV. The dental X-Ray image is fed to the image processing module that processes the image to highlight the feature points which are essential for cavity determination. Once these feature points are calculated and highlighted, these points are then fed to AI module to determine the presence of cavity, if found. Additionally, these points are used to further train the system for continuous learning i.e. Machine Learning. The mode of learning in this project is supervised. The final output of the system is the highlighted boundary around the cavity, if found, or system provides the message of “no cavity detected”.
A Raspberry Pi based system using Python and OpenCV as the platform for the developed application. The application is equipped with Digital Image Processing module as well as Artificial Intelligence based learning module for effective localization of dental cavity.

| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry Pi 4 B | Equipment | 1 | 15000 | 15000 |
| LCD Screen | Equipment | 1 | 10000 | 10000 |
| Keyboard and Mouse | Equipment | 1 | 2000 | 2000 |
| Raspberry Pi Power Supply | Equipment | 1 | 1000 | 1000 |
| 32GB Memory Card | Equipment | 1 | 2000 | 2000 |
| VGA Cable | Equipment | 1 | 400 | 400 |
| HDMI to VGA Converter | Equipment | 1 | 400 | 400 |
| Documentation | Miscellaneous | 2 | 2000 | 4000 |
| Total in (Rs) | 34800 |
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