Building feature extraction method based on double reflection imaging dictionary
نویسندگان
چکیده
منابع مشابه
Automatic Extraction of Subcategorization Frames for Corpus-based Dictionary-building
This paper presents a method for automatically extracting subcorpora isolating different subcategorization frames for nouns, adjectives, and verbs in the 100 mi. word BNC. The tool is being used in the FrameNet project, an NSFfunded project that is involved in producing a database and tools for dictionary-building, based on the principles of Frame Semantics. The subcorpora are used (1) to facil...
متن کاملA Fast Localization and Feature Extraction Method Based on Wavelet Transform in Iris Recognition
With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This rese...
متن کاملA Robust Wavelet Based Feature Extraction Method
In this paper, we propose a wavelet based feature extraction method with a high tolerance to white Gaussian noise. This method is also computationally efficient. Along with an HMM classifier, this method is used for face recognition. High recognition rates in the presence of white Gaussian noises with different variances show this technique as a promising feature extraction method.
متن کاملA Fast Texture Feature Extraction Method Based on Gabor Wavelets
With the development of computer vision, robots need to detect target objects from image sequence for autonomous navigation. To identify targets, the perceptual system of autonomous robots first needs to segment the images into nonoverlapping but meaningful regions based on low-level features such as color, texture measures and shapes etc.. Being an important component, Gabor wavelets are often...
متن کاملA method for speeding up feature extraction based on KPCA
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop a novel method to improve KPCA-based feature extraction. The developed method is the first one that is methodologically consistent with KPCA. Experiments on several benchmark datasets illustrate that the feature extrac...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: EURASIP Journal on Wireless Communications and Networking
سال: 2019
ISSN: 1687-1499
DOI: 10.1186/s13638-019-1530-1