TOP 5 IMAGE PROCESSING PROJECTS || Best Image Processing Projects || Image Processing Projects

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TOP 5 IMAGE PROCESSING PROJECTS IDEAS FOR ENGINEERING STUDENTS.

1) Facial Expression Emotion Recognition
Facial expression emotion recognition is the task of detecting emotions in an individual's face, typically through image processing and machine learning algorithms. The goal is to automatically classify emotions such as happiness, sadness, anger, fear, surprise, disgust, and neutral, based on the facial features such as wrinkles, eyebrows position, mouth shape, etc.

2) Real Time Face Recognition
Real-time face recognition refers to the ability to identify and verify an individual's identity in real-time using a camera and computer vision algorithms. The process involves capturing an image or video of a person's face, detecting the face within the image, and then comparing it to a database of known faces to find a match.

3)Hand Gesture Recognition
Hand gesture recognition is a field of computer vision that deals with detecting and interpreting hand movements and gestures made by a user. This technology can be used for human-computer interaction in a variety of applications such as gaming, virtual reality, sign language recognition, and others. Hand gesture recognition systems typically involve the use of cameras or depth sensors to capture the movements of a person's hands, followed by image processing and machine learning algorithms to identify and classify the gesture.

4)Currency Recognition
Currency recognition refers to the ability of a computer system to identify and process banknotes or coins of different denominations. This technology has applications in various fields such as banking, retail, and self-service kiosks. Currency recognition systems typically involve image processing and machine learning algorithms to identify the denomination, country, and possibly other features of a banknote or coin, such as its serial number.

5)Image Denoising
Image denoising is the process of removing or reducing noise from an image. Noise in images can be caused by various factors such as image sensors, compression, transmission, or storage. Image denoising is an important step in many computer vision and image processing applications, as noise can have a significant impact on the quality of the image and the performance of subsequent processing steps.

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