Performance Analysis of Fingerprint Denoising Using Stationary Wavelet Transform

Abstract

Abstract-The present decade has seen the growth of both, the software and hardware for three dimensional televisions in real time applications. Depth map is fundamental key of 3-Dimensional algorithms. Reliable depth map is an acceptance in 3D transmission, analysis and compression of algorithm. Computer vision and pattern recognition research fields use sensor like low cost Microsoft kinect. Kinect sensor suffers from some problems of noise, poor accuracy and unmatched edges. This paper presents effective solution to improve the real time depth sequences and real time 3-D map using warping method from kinect sensor.We proposed real time frequency domain based depth data refurbishment and improve the quality of depth video provided by sensors' Microsoft Kinect. The quality of the depth map is improved by depth refurbishment in frequency domain technique, filling the holes present in the maps, 2-Dimensional spatial filtering and permutation of morphological operation. We show that the proposed approach is able to generate high quality depth maps which can be quite useful in improving the performance of various applications of Microsoft Kinect such as obstacle detection and avoidance, pose estimation, gesture recognition, skeletal and facial tracking, etc. We produce the real time 3-D map using warping method. An experimental result shows that the quality of our proposed method is better than previous research works. Our algorithm produces noise less, reliable, smooth and efficient depth sequence. The qualitative parameter Peak Signal to Noise Ratio (PSNR), Structure Similarity Index Map (SSIM) and Mean Square Error (MSE) measure the real time results for comparative analysis.

Detection Algorithm of Wind Power Equipment Video Image Sequence Based on Artificial Intelligence

“…e gray level of pixels is selected, and the initial background is extracted by comparing the continuous sequence of frame images (such as average or median method). e other is based on statistical modeling, Gaussian mixture distribution, and other methods [19,20].…”

“…It is the basic form of using a common display to display the actual effect of expansion. In this mode, the user uses the camera to obtain the real-world image processed by the computer graphics system, adds or superimposes the corresponding computer processing virtual image or model according to the actual world image, and displays it on the monitor [18,19].…”