Studi Pencocokan Plat Kendaraan Dengan Metode Phase Only Correlation

Salah satu cara pengenalan kendaraan adalah dengan identifikasi plat. Umumnya identifikasi yang dilakukan mengacu pada proses segmentasi tiap karakter dari citra plat. Makalah ini mengajukan suatu metode identifikasi plat yang sederhana tanpa melakukan pengenalan melainkan langsung pada proses pencocokan yang berbasis Phase Only Correlation (POC). POC mencocokkan plat dengan mengorelasikan fasa dari dua citra plat. Fasa diperoleh dengan mengubah citra dari domain spasial menjadi domain frekuensi menggunakan Transformasi Fourier Waktu Diskrit (TFWD). Nilai puncak POC akan tinggi jika citra plat yang dicocokkan adalah citra yang berasal dari plat yang sama. Sebaliknya akan rendah jika yang dicocokkan berasal dari plat yang berbeda. Hasil simulasi menggunakan 20 citra plat menunjukkan bahwa metode POC dapat digunakan dalam pencocokan citra plat

An LBP based Iris Recognition System using Feed Forward Back Propagation Neural Network

An iris recognition system using LBP feature extraction technique with Feed Forward Back Propagation Neural Network is presented. For feature extraction from the eye images the iris localization and segmentation is very important task so in proposed work Hough circular transform (HCT) is used to segment the iris region from the eye mages. In this proposed work Local Binary Pattern (LBP) feature extraction technique is used to extract feature from the segmented iris region, then feed forward back propagation neural network is use as a classifier and in any classifier there to phases training and testing. The LBP feature extraction technique is a straightforward technique and every proficient feature operator which labels the pixels of an iris image by thresholding the neighbourhood of each pixel and considers the feature as a result in form of binary number. Due to its discriminative efficiency and computational simplicity the LBP feature extractor has become a popular approach in various recognition systems. This proposed method decreased the FAR as well as FRR, & has increases the system performance on the given dataset. The average accuracy of proposed iris recognition system is more than 97%

Sift Algorithm for Iris Feature Extraction

Iris recognition is proving to be one of the most reliable biometric traits for personal identification In fact iris patterns have stable invariant and distinctive features for personal identification Reliable authorization and authentication are becoming necessary for many everyday applications Iris recognition has been paid more attention due to its high reliability in personal identification But iris feature extraction is easily affected by some practical factors such as inaccurate localization occlusion and nonlinear elastic deformation The objective of the study and proposed work is to adapt the increasing usage of biometric systems which can reduce the iris preprocessing and describe iris local properties effectively and have encouraging iris recognition performance This work presents an efficient algorithm of iris feature extraction based on modified scale invariant feature transform algorithm SIF

Limited-data automatic speaker verification algorithm using band-limited phase-only correlation function

In this paper, a new method to deal with automatic speaker verification based on band-limited phaseonly correlation (BLPOC) is proposed. The aim of this study is to validate the use of the BLPOC function as a new limited-data automatic speaker verification technique. Although some speaker verification techniques have high accuracy, efficiency usually depends on the extraction of complex theoretical information from speech signals and the amount of the data for training the algorithms. The BLPOC function is a high-accuracy biometric technique traditionally implemented in human identification by fingerprints (through image-matching)

Acoustic individual identification in birds based on the band-limited phase-only correlation function

A new technique based on the Band-Limited Phase-Only Correlation (BLPOC) function to deal with acoustic individual identification is proposed in this paper. This is a biometric technique suitable for limited data individual bird identification. The main advantage of this new technique, in contrast to traditional algorithms where the use of large-scale datasets is assumed, is its ability to identify individuals by the use of only two samples from the bird species. The proposed technique has two variants (depending on the method used to analyze and extract the bird vocalization from records): automatic individual verification algorithm and semi-automatic individual verification algorithm. The evaluation of the automatic algorithm shows an average precision that is over 80% for the identification comparatives. It is shown that the efficiencies of the algorithms depend on the complexity of the vocalizations

Studi Pencocokan Plat Kendaraan Dengan Metode Phase Only Correlation

Salah satu cara pengenalan kendaraan adalah dengan identifikasi plat. Umumnya identifikasi yang dilakukan mengacu pada proses segmentasi tiap karakter dari citra plat. Makalah ini mengajukan suatu metode identifikasi plat yang sederhana tanpa melakukan pengenalan melainkan langsung pada proses pencocokan yang berbasis Phase Only Correlation (POC). POC mencocokkan plat dengan mengorelasikan fasa dari dua  citra plat. Fasa diperoleh dengan mengubah citra dari domain spasial menjadi domain frekuensi menggunakan Transformasi Fourier Waktu Diskrit (TFWD). Nilai puncak POC akan tinggi jika citra plat yang dicocokkan adalah citra yang berasal dari plat yang sama. Sebaliknya akan rendah jika yang dicocokkan berasal dari plat yang berbeda. Hasil simulasi menggunakan 20 citra plat menunjukkan bahwa metode POC dapat digunakan dalam pencocokan citra plat

Locating regions of interest prior to X-ray imaging using stereo-photogrammetry

The research project aims at locating regions of interest (ROIs) on human subjects prior to X-ray imaging on the Lodox Statscan whole body imaging system