Matlab Project Lung Cancer Detection Using Neural Network Full Source Code || IEEE Based Project

ABSTRACT

             In today’s world ,image processing methodology is very rampantly used in several medical fields for image improvement which helps in early detection and analysis of the treatment stages ,time factor also plays a very pivtol role in discovering the abnormality in the target images like-lung cancer ,breast cancer etc. this research focuses upon image quality and accuracy. image quality assessment as well as improvement are dependent upon enhancement stage where low pre-processing techniques are used based upon gabor filter within Gaussian rules; thereafter the segmentation principles are applied over the enhanced region of the image and the input for feature extraction is obtained, further depending upon the general features, a normality comparison is made .in the following research the crucial detected features for accurate image comparison are pixel percentage and masking labelling. In this research we have done classification based upon artificial neural networks which is more satisfactory than other current classification methods.

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Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Emotion and Gender Recognition Using Image Processing Matlab Project with Source Code || IEEE Based Project || Final Year Project

ABSTRACT

              The most important and impressive biometric feature of human being is the face. It conveys various information including gender, ethnicity etc. Face information can be applied in many sectors like biometric authentication and intelligent human-computer interface. Many potential applications such as human identification, smart human computer interface, computer vision approaches for monitoring people, passive demographic data collection, and etc needs a successful and dependable classification method. It is really a very challenging job to detect male or female accurately separating two sets of data. So it is very urgent to have a reliable classifier to improve the classification performance.This project presents an approach to extract effective features for face detection and gender classification system. In various biometric applications, gender recognition from facial images plays an important role. In this project gender recognition image sequence have been successfully investigated. Gender recognition plays an important role for a wide range of application in the field of Human Computer Interaction. The system comprises two modules: a face detector and a gender classifier. The human faces are first detected and localized in the input image. Each detected face is then passed to the gender classifier to determine whether it is a male or female.

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Detection of Cardiac Disease from ECG Signal Matlab Project with Source Code || IEEE Based Project

ABSTRACT

            Modern day lifestyle and our ignorance towards health have put the most vital organ of our body Heart at great risk. India today is witnessing a lot many young people suffering from heart diseases which even lead to untimely demise. Most common heart abnormality includes arrhythmia which is nothing but irregular beating of heart. Going by the trend/statistics, middle aged people (30-45yrs) are at great risk because of high stress in both personal and professional lives. This necessitates the need for a system which can not only detect any anomaly in functioning of our heart but warns us against any threat. Our project is based on developing such a system that can give us prior information about the upcoming threat or the heart disease which we are prone to. Cardiac arrhythmia is a major kind of abnormal heart activity. An arrhythmia is a problem with the heartbeat rate or rhythm of the heartbeat. For the period of an arrhythmia, the heart may beat too fast or too slow, or with an irregular rhythm. Fast heartbeat is said to be tachycardia whereas slow is called Bradycardia. Classification of cardiac arrhythmia is a difficult task. One of the ways to detect cardiac arrhythmia is to use electrocardiogram (ECG) signals. The ECG is the most important biomedical-signal used by cardiologists for diagnostic purposes. The ECG signal provides all the required information about the electrical activity of the heart. The early detection of the cardiac arrhythmias can save lives and enhance the quality of living through appreciates treatment.

PROJECT OUTPUT

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Matlab Project Age and Gender Recognition Using Image Processing full Source Code || IEEE Based Project

ABSTRACT

               In this project, a fast and efficient gender and age estimation system based on facial images is developed. There are many methods have been proposed in the literature for the age estimation and gender classification. However, all of them have still disadvantage such as not complete reflection about face structure, face texture. We classified the gender and age based on the association of two methods: geometric feature based method and Principal Component Analysis (PCA) method for improving the efficiency of facial feature extraction stage. The face database contains the 13 individual groups. Within a given database, all weight vectors of the persons within the same age group are averaged together. Experimental results show that better gender classification and age estimation. Gender classification is important visual tasks for human beings, such as many social interactions critically depend on the correct gender perception. As visual surveillance and human-computer interaction technologies evolve, computer vision systems for gender classification will play an increasing important role in our lives. Age prediction is concerned with the use of a training set to train a model that can estimate the age of the facial images.

PROJECT OUTPUT

PROJECT VIDEO

Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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