Malaria detection using OpenCV

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Malaria detection using OpenCV

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Malaria caused by the parasite commonly infects a certain type of mosquito, It will cause severe fever, flu, headache, etc. In this project, we are going to detect Malaria using the medical image of the persons, whether they infected by malaria or not. we are using Deep learning to identify malaria from the medical image.CNN (Convolutional Neural Network) is one of the deep learning algorithms for classification, which identifies its features by itself by studying the given set of images which is known as dataset

Existing system

In the existing system, malaria is detected by using the normal OpenCV algorithm, in which we have to specify the featuring to classify that images

Proposed system

In the proposed system CNN a deep learning algorithm is used, which it will classify the image by identifying the features on its own. It has several layers which the images pass by. On passing each layer, the feature of the image will be identified and class will be displayed. It includes bias and weights.

Project description

In this project, the dataset is collected from various sources and segregated into two sections such as Malaria infected and Malaria Non-infected. Then CNN layers are designed to classify the image based on its features. Training will be done to the collected dataset to generate a model file that has good accuracy. The same model will be loaded and image needs to be classified will be passed to the trained model to make a classification. Accuracy can be increased by providing more images on each category


In this project, though we have used fewer images accuracy is more than 95 percent on training.


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