Analysis of Digital Signal Features Extraction Based on LBP Operator

Abstract

Digital voice signal is one of the most widely used type of digital data, it is an important and applicable type of data, & it is used in various applications such human identification systems. Digital voice file usually has a big Size, which means increasing the complexity of the recognition system and decreasing the identification system efficiency. To simplify the recognition system and to increase the system efficiency and accuracy we will introduce a method based on LBP to create a unique voiceprint for each wave file, these voiceprints can be used in a recognition system to identify the person and the spoken voice, we will also discuss how the wave file parameters such as amplitude and sampling rate affect the voiceprint.

Window averaging to create LBP features for a color image

“…Multiple methods [19]-[21] are used to extract the features of the digital image, and what we are interested in here is the methods based on the local binary byte (LBP) method [22]- [24]. LBP method can be used to extract a unique features victor for each color image, this method can be implemented by comparing each pixel with the 8_neighbors, and depending on the results of comparison generate a binary number, this number then is to be converted to decimal, then 1 must be added the repetition of this number to form a features victor with values point to the repetition of each decimal value (from 0 to 255) as shown in Figures 5 and 6.…”