Projects Category: Image

In this project, a formant analyzer and visualizer application was developed to analyze and display the spectral characteristics of speech signals. By extracting the formant frequencies from audio recordings, the application aimed to provide a better understanding of speech production and perception. This tool could be beneficial for various fields, such as linguistics, speech therapy, and voice recognition technology. By visualizing the formant patterns, users can gain insights into the nuances of speech and further enhance their knowledge in related areas.

This project focused on the development of a 3D scanning system that utilized photogrammetry techniques to generate accurate and detailed 3D models of objects and environments. The system aimed to provide high-resolution 3D models by capturing a series of 2D images from various angles and processing them through advanced algorithms. Potential applications of this technology include digital archiving, heritage preservation, virtual reality, and product design.

This project aimed to develop an advanced gait analysis application that could accurately measure and analyze an individual’s walking pattern. By utilizing various techniques such as computer vision, machine learning, and sensor fusion, the application was designed to provide valuable insights into an individual’s biomechanics, balance, and overall gait health. The collected data could be used to detect and diagnose gait abnormalities, monitor rehabilitation progress, and assist in optimizing athletic performance. This application could prove invaluable for healthcare professionals, sports trainers, and researchers working in fields related to human movement and biomechanics.

This project involved the development of a crack detection system using U-Net deep learning architecture and NVIDIA Jetson Nano hardware. By employing advanced computer vision and machine learning techniques, the system aimed to accurately identify and localize cracks in various structures, thereby enabling timely maintenance and reducing the risk of catastrophic failures.

The objective of this project was to develop a mixed reality app that provided an immersive and interactive presentation experience. By leveraging the latest advancements in mixed reality technology, the app aimed to revolutionize the way presentations are conducted, improving audience engagement and understanding.

This project focused on the development of a transparent A-Pillar algorithm to improve driver visibility and safety. By combining advanced computer vision techniques and real-time image processing, the algorithm aimed to eliminate blind spots caused by the A-Pillar, thus reducing the risk of accidents and enhancing overall driving safety.

In this project, an app was developed to animate 2D images using live or stored video data as a reference. The app aimed to provide a unique and engaging user experience, with potential applications in filmmaking, video conferencing, and preserving user privacy. The project explored advanced computer vision techniques to ensure smooth and realistic animation of static images, overcoming potential distortions and inaccuracies.

This project involved the creation of a connector app to integrate the Magento and Shopify e-commerce platforms. By enabling streamlined synchronization of product data, inventory, and orders between the two platforms, the connector app aimed to simplify the management of online stores and improve overall operational efficiency. This solution could potentially save merchants time and effort, allowing them to focus on growing their businesses.