The method of micro-motion cycle feature extraction based on confidence coefficient evaluation criteria

2017 ◽  
Author(s):  
Ren Hongmei ◽  
Jing Huang ◽  
Tang Chuanzi ◽  
Bo Li
Keyword(s):  
Feature Extraction ◽  
Evaluation Criteria ◽  
Confidence Coefficient ◽  
Micro Motion

scholarly journals Micro-Motion Feature Extraction of a Rotating Target Based on Interrupted Transmitting and Receiving Pulse Signal in an Anechoic Chamber

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1028
Author(s):  
Feng Zhao ◽  
Xiaobin Liu ◽  
Zhiming Xu ◽  
Yuan Liu ◽  
Xiaofeng Ai
Keyword(s):  
Feature Extraction ◽  
Coupling Effect ◽  
Pulse Repetition Frequency ◽  
Pulse Signal ◽  
Anechoic Chamber ◽  
Repetition Frequency ◽  
Motion Feature ◽  
Whole Process ◽  
Micro Motion ◽  
Rotating Target

The pulse signal is widely used in micro-motion feature extraction of rapidly rotating targets as its pulse repetition frequency (PRF) can be high. However, when the pulse signal is implemented in a range-limited anechoic chamber for micro-motion feature extraction, the transmitted and reflected pulse signals may be coupled at the receiver. To solve this problem, the interrupted transmitting and receiving (ITR) method is applied to transmit the pulse signal with hundreds of sub-pulses. The target echo can be received when the sub-pulse is not transmitted. Hence, it avoids the coupling effect of transmitted signals and echoes. Then, the whole process of micro-motion feature extraction for rotating target is proposed based on the ITR method. At last, the simulations and experiments verify that the rotating target micro-Doppler can be extracted by the ITR pulse signal.

An Efficient Retinal Vessels Biometric Recognition System by Using Multi-Scale Local Binary Pattern Descriptor

2020 ◽  
Vol 10 (10) ◽  
pp. 2481-2489
Author(s):  
Muhammad Sheraz Arshad Malik ◽  
Qoseen Zahra ◽  
Imran Ullah Khan ◽  
Muhammad Awais ◽  
Gang Qiao
Keyword(s):  
Feature Extraction ◽  
Random Forest ◽  
Efficient Method ◽  
Large Scale ◽  
Local Binary Pattern ◽  
Evaluation Criteria ◽  
Recognition System ◽  
Suggested Approach ◽  
Multi Scale ◽  
Biometric Systems

Biometric systems are technically used for human recognition by identifying the unique features of an individual. Many security issues are found related to biometric systems such as voice, fingerprints, face, iris, signatures, etc., but the retina is a unique and efficient method to identify valid one. The aim of this paper is provided with an efficient method to recognize someone based on unique retina features. A proposed system based on retinal blood vessel pattern by using multi-scale local binary pattern (MSLBP) and random forest (Bagging tree) as feature extraction and classification. MSLBP is an efficient method to extracted features at six scales perpixel level, earlier work found the deficiency based on simple binary pattern with coverage of small areas and per-pixel level in the surrounding. MSLBP and random forest classifier suggested approach use for improving usability, perceivability, and sensitivity on large scale areas. It is the fastest method to get features accurately in an efficient way at every level of pixels. This method based on deep learning evaluation (criteria) parameter selection that provides more significant influence with sharp feature extraction on large scale areas based on seconds and improves the efficiency of images. MSLBP overcomes the problem of image sizing, pixel levels and efficiently provide accurate results.

scholarly journals Micro-motion feature extraction of narrow-band radar target based on ROMP

2019 ◽  
Vol 2019 (21) ◽  
pp. 7860-7863
Author(s):  
Shuai Chen ◽  
Cunqian Feng ◽  
Xuguang Xu
Keyword(s):  
Feature Extraction ◽  
Narrow Band ◽  
Radar Target ◽  
Motion Feature ◽  
Micro Motion

scholarly journals Analysis and Research on Radar Gesture Micro-motion Feature Extraction Method

2021 ◽  
Vol 2031 (1) ◽  
pp. 012012
Author(s):  
Yaoyao Dong ◽  
Wei Qu ◽  
Tianhao Gao ◽  
Pengda Wang ◽  
Haohao Jiang
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Motion Feature ◽  
Feature Extraction Method ◽  
Micro Motion
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