Top 10 Image processing projects in 2022

Skin cancer detection using Deep learning

Skin cancer is one of the most prevalently seen cancer type in human beings. Skin cancer occurs due to the uncontrollable growing of mutations taking place in DNAs owing to some reasons. Recognizing the cancer in early stages could increase the chance of a successful treatment. Nowadays, computer aided diagnosis applications are used almost at every field. One of the mostly used areas is health sector. 

Attendance Marking System Using Matlab

In this project we design an  Automated Attendance marking system with the help of facial recognition owing to the difficulty in the manual as well as other traditional means of attendance system. This system uses viola jones algorithm to detect faces and LBP and PCA feature extraction techniques.CNN is used for classification.

Real time face emotion recognition using deep learning- Matlab

In this deep learning projects, a deep learning model is used for prediction of expressions of both still images and real time video. However, in both the cases we have to provide image to the model. In case of real time video the image should be taken at any frame in time and feed it to the model for prediction of expression. The system automatically detects the face using HAAR cascade then its crops it and resize the image to a specific size and give it to the model for prediction.

COVID-19 Detection in Xray Images using Matlab

Coronaviruses are important human and animal pathogens. To date the novel COVID-19 coronavirus is rapidly spreading worldwide and subsequently threatening health of billions of humans. Clinical studies have shown that most COVID-19 patients suffer from the lung infection. Although chest CT has been shown to be an effective imaging technique for lung-related disease diagnosis, chest Xray is more widely available due to its faster imaging time and considerably lower cost than CT. 

Sign Language Recognition using Densenet-Deep Learning Approach

Sign language is used by deaf and hard hearing people to exchange information between their own community and with other people. Computer recognition of sign language deals from sign gesture acquisition and continues till text/speech generation. Sign gestures can be classified as static and dynamic. However static gesture recognition is simpler than dynamic gesture recognition but both recognition systems are important to the human community. 

Leaf disease detection using CNN-Deep learning

In this Image processing project a deep learning-based model is proposed ,Deep neural network is trained using public dataset containing images of healthy and diseased crop leaves. The model serves its objective by classifying images of leaves into diseased category based on the pattern of defect.

Kidney stone detection using Matlab

The Kidney stones are one of the most common disorders of the urinary tract. Kidney stone problem occurs as a common problem to every men and woman , due to nature of living. A kidney stone termed as renal calculi is a solid piece of material that forms in a kidney when substances that are normally found in the urine become highly concentrated. 

Lung Cancer Detection using Deep Learning

In recent years, so many Computer Aided Diagnosis (CAD) systems are designed for diagnosis of several diseases. Lung cancer detection at early stage has become very important and also very easy with image processing and deep learning techniques. In this study lung patient Computer Tomography (CT) scan images are used to detect and classify the lung nodules and to detect the malignancy level of that nodules. The CT scan images are segmented using CNN architecture. 

Food Calorie Measurement Using Matlab

High calorie intake has proved harmful worldwide, as it has led to many diseases. However, dieticians have mistake that a standard intake of number of calories is essential to maintain the right balance of calorie content in human body. In this thesis, we consider the category of tools that use image processing to recognize single and multiple mixed food objects, namely support vector machine (SVM). 

This site is not a part of the Facebook™ website or Facebook™ Inc. Additionally, This site is NOT endorsed by Facebook™ in any way. FACEBOOK™ is a trademark of FACEBOOK™, Inc. All of my terms, privacy policies and disclaimers  can be accessed via the links. We feel transparency is important and we hold ourselves (you & me) to a high standard of integrity. Thanks for stopping by. We hope this training and content brings you a lot of value & results.