This article presents 11 biometric-based system design solutions, including gesture recognition, iris recognition, voiceprint recognition, and more, for your reference. These systems are designed to enhance user interaction and improve the accuracy of identification processes.
**Design of an Intelligent Input System Based on Gesture Recognition**
The Smartmouse intelligent gesture input system consists of a handheld terminal (gesture data acquisition module) and a host terminal (data reception and processing module). The two components communicate wirelessly, allowing the handheld device to be worn on the user’s finger for convenient gesture data collection. The host side can interface with a PC, receiving and intelligently processing the gesture data for real-time interaction.
**Design of a Gesture Recognition TV Remote Control Based on DSP**
Traditional TV remote controls rely on mechanical buttons, which lack interactivity and entertainment value. To address this, a gesture recognition algorithm based on the DSP2812 is developed. By converting the user's gesture motion into corresponding infrared signals, the system enables users to change channels and adjust volume using hand gestures, enhancing the overall viewing experience.
**Gesture Recognizer Terminal Design**
This system uses the values from a three-axis accelerometer to identify six predefined postures. Each axis is sampled separately, collecting 50 data points per sample. The data is then processed individually to detect if a predefined action has occurred, making it suitable for applications such as motion control and interactive gaming.
**Portable EMG Signal Acquisition and Human Body Motion Recognition Design**
This system acquires surface electromyography (sEMG) signals through electrode sheets placed on the skin. This non-invasive method is simple, safe, and widely used in medical and assistive technology applications. It allows for the recognition of human body movements by analyzing muscle activity.
**DIY Your Somatosensory Game: Human Motion Recognition System**
This project utilizes the Virtex-5 OpenSPARC evaluation platform. It starts by decoding video stream data from a PC using a VGA decoder chip, extracting RGB values along with field and line signals. A digital camera (OV7670) captures human hand movements, and image processing algorithms determine the current motion. The processed data is then superimposed with RGB signals and sent via DVI interface to a display, enabling real-time motion tracking and interaction.
**ST Micro MEMS Module for Custom Action Recognition**
The LSM330 module integrates a 3-axis digital gyroscope, a 3-axis digital accelerometer, and two embedded finite state machines. This allows for custom action recognition within the module itself, making it ideal for wearable devices and motion-sensitive applications.
**Design of a Universal Voice Control System Based on Voiceprint Recognition**
This system aims to create a more general voice-controlled interface. For demonstration purposes, it uses Chinese pronunciations of numbers (0–9) to control commands in a Linux environment. Users can issue commands by speaking the corresponding number, enabling efficient and intuitive control over various system functions.
**FPGA-Based Speaker Recognition System, Including Schematic and Source Code**
This paper explores speaker recognition using speech signals. Unlike other biometric methods, speech recognition requires no special hardware—common devices like microphones and phones can be used. This approach is more convenient, accurate, and scalable, making it ideal for security and personalization applications.
**Design of a Chaotic Encryption Iris Recognition System Based on FPGA**
A portable FPGA-based embedded iris recognition system is developed. It includes modules for power management, image acquisition, image processing, memory, user interaction, and network transmission. The system is designed from hardware, software, and algorithmic perspectives, ensuring high security and efficiency.
**Hardware Design and Implementation of a Hot Iris Recognition System**
This paper describes the implementation of an iris recognition system using a Spartan-3E development board. It covers the entire process, from iris image acquisition and localization to feature extraction, database creation, classifier design, and image matching. The results of the recognition process are also presented.
**Research and Implementation of a Creative Ear Pattern Recognition System**
This design leverages SOPC technology to simplify the system architecture and improve stability. Using VHDL programming, high-speed data acquisition is achieved through hardware, reducing the processor's workload. The system performs fast ear pattern image acquisition and DSP-based data processing, improving the quality of the input image and enhancing the accuracy of feature extraction.
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