Real-Time Enhancement Method of Low Gray Image Under Dark Background

2011 ◽  
Vol 26 (3) ◽  
pp. 374-378
Author(s):  
黄梅 HUANG Mei ◽  
吴志勇 WU Zhi-yong ◽  
梁敏华 LIANG Min-hua ◽  
于建军 YU Jian-jun ◽  
管目强 GUAN Mu-qiang
Keyword(s):  
Real Time ◽  
Gray Image ◽  
Dark Background ◽  
Enhancement Method

Wital: WiFi-based Real-time Vital Signs Monitoring During Sleep

2021 ◽  
Author(s):  
Yu Gu ◽  
Xiang Zhang ◽  
Huan Yan ◽  
Zhi Liu ◽  
Fuji Ren
Keyword(s):  
Real Time ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Implementation Process ◽  
Sleep Monitoring ◽  
Daily Lives ◽  
Vital Signs Monitoring ◽  
Quality Sleep ◽  
Enhancement Method ◽  
Positioning Algorithm

High-quality sleep is essential to our daily lives, and real-time monitoring of vital signs during sleep is beneficial. Current sleep monitoring solutions are mostly based on wearable sensors or cameras, the former is worse for sleep quality, the latter is worse for privacy, dissimilar to such methods, we implement our sleep monitoring system based on COTS WiFi devices. There are two challenges need to be overcome in the system implementation process: First, the torso deformation caused by breathing/heartbeat is weak, how to effectively capture this deformation? Second, movements such as turning over will affect the accuracy of vital signs monitoring, how to quickly distinguish such movements? For the former, we propose a motion detection capability enhancement method based on Rice-K theory and Fresnel theory. For the latter, we propose a sleep motion positioning algorithm based on regularity detection. The experimental results indicated the performance of our method.

Wave Equalization - A New Image Enhancement Method for Gray Image Binarization under Uneven Illumination

2014 ◽  
Vol 631-632 ◽  
pp. 470-473
Author(s):  
Wei Wei
Keyword(s):  
Image Enhancement ◽  
Image Binarization ◽  
Uniform Illumination ◽  
Excellent Performance ◽  
Gray Image ◽  
3D Terrain ◽  
Enhancement Method ◽  
Pca Algorithm

The gray image can be viewed as a 3D terrain consisting of intensity waves. The Wave Equalization introduced in the paper is to weaken the influence of uneven illumination on the gray image binarization. The 2D wave is decomposed into several 1D waves corresponding to different directions for 1D equalization. Then PCA algorithm is used to compress all 1D results to the final image with uniform illumination. The extensive experiments in the paper had proved that our method has excellent performance and adaptability for various uneven illumination environments.

scholarly journals Wital: WiFi-based Real-time Vital Signs Monitoring During Sleep

2021 ◽  
Author(s):  
Yu Gu ◽  
Xiang Zhang ◽  
Huan Yan ◽  
Zhi Liu ◽  
Fuji Ren
Keyword(s):  
Real Time ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Implementation Process ◽  
Sleep Monitoring ◽  
Daily Lives ◽  
Vital Signs Monitoring ◽  
Quality Sleep ◽  
Enhancement Method ◽  
Positioning Algorithm

High-quality sleep is essential to our daily lives, and real-time monitoring of vital signs during sleep is beneficial. Current sleep monitoring solutions are mostly based on wearable sensors or cameras, the former is worse for sleep quality, the latter is worse for privacy, dissimilar to such methods, we implement our sleep monitoring system based on COTS WiFi devices. There are two challenges need to be overcome in the system implementation process: First, the torso deformation caused by breathing/heartbeat is weak, how to effectively capture this deformation? Second, movements such as turning over will affect the accuracy of vital signs monitoring, how to quickly distinguish such movements? For the former, we propose a motion detection capability enhancement method based on Rice-K theory and Fresnel theory. For the latter, we propose a sleep motion positioning algorithm based on regularity detection. The experimental results indicated the performance of our method.

scholarly journals GESTURE RECOGNITION SYSTEM

2012 ◽  
pp. 125-130
Author(s):  
ANUBHAV SRIVASTAVA ◽  
PRANSHI AGARWAL ◽  
SWATI AGARWAL ◽  
USHA SHARMA
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Recognition System ◽  
Skin Colour ◽  
Hand Gesture ◽  
Input Device ◽  
Skin Detection ◽  
Dark Background

In this paper, the hand gesture of a person is recognised and it identifies which hand of the person is raised. The skin colour is taken to recognise hands and face and the dark background is taken so that the skin detection may become easier. The hands and face are differentiated on the basis of area and centroid. Camera is the only input device used in this algorithm. No other input device is used to differentiate hands from the remaining body. This algorithm can be used both on the captured images and real time images.

scholarly journals Pressure Signal Enhancement of Slowly Increasing Leaks Using Digital Compensator Based on Acoustic Sensor

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4317
Author(s):  
Fang Wang ◽  
Weiguo Lin ◽  
Zheng Liu ◽  
Xianbo Qiu
Keyword(s):  
Frequency Response ◽  
Real Time ◽  
Response Analysis ◽  
Acoustic Sensor ◽  
Frequency Response Analysis ◽  
Pipeline Transportation ◽  
Safety Protection ◽  
Enhancement Method ◽  
Adaptive Adjustment ◽  
Detection Technologies

Pipeline leak detection technologies are critical for the safety protection of pipeline transportation. However, they are insensitive to slowly increasing leaks. Therefore, this study proposes an enhancement method for slowly increasing leak signals. By analyzing the characteristics of pressure signals of slowly increasing leaks, a digital compensator is developed to overcome the disadvantages of pressure signals and enhance the pressure signals. According to the frequency response analysis of the digital compensator, the enhancement principle is the parameter adjustment of the digital compensator. Therefore, this paper further proposes an adaptive adjustment method of the parameter to enhance different degrees of leak signals online in real-time, and the proposed method is evaluated using two field pipelines. The experimental results demonstrate that this method is suitable not only for enhancing slowly increasing leaks but also for enhancing abrupt leaks.

scholarly journals Lightweight Feature Enhancement Network for Single-Shot Object Detection

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1066
Author(s):  
Peng Jia ◽  
Fuxiang Liu
Keyword(s):  
Receptive Field ◽  
Object Detection ◽  
Real Time ◽  
Detection System ◽  
Field Enhancement ◽  
Detection Performance ◽  
Feature Representation ◽  
Data Sets ◽  
Single Shot ◽  
Enhancement Method

At present, the one-stage detector based on the lightweight model can achieve real-time speed, but the detection performance is challenging. To enhance the discriminability and robustness of the model extraction features and improve the detector’s detection performance for small objects, we propose two modules in this work. First, we propose a receptive field enhancement method, referred to as adaptive receptive field fusion (ARFF). It enhances the model’s feature representation ability by adaptively learning the fusion weights of different receptive field branches in the receptive field module. Then, we propose an enhanced up-sampling (EU) module to reduce the information loss caused by up-sampling on the feature map. Finally, we assemble ARFF and EU modules on top of YOLO v3 to build a real-time, high-precision and lightweight object detection system referred to as the ARFF-EU network. We achieve a state-of-the-art speed and accuracy trade-off on both the Pascal VOC and MS COCO data sets, reporting 83.6% AP at 37.5 FPS and 42.5% AP at 33.7 FPS, respectively. The experimental results show that our proposed ARFF and EU modules improve the detection performance of the ARFF-EU network and achieve the development of advanced, very deep detectors while maintaining real-time speed.

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