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Öğe Palmprint recognition based gabor wavelet transform using K-NN classification(European Journal of Technique (EJT), 2016-04-01) Çalışkan, AbidinPalmprint recognition system is regarded as the reliable and accurate biometric identification system available. Viewed in the palmprint recognition system of biometric approaches, compared to other models because it is a new handheld biometric feature recognition system has recently attracted the attention of researchers. In this study, palmprint recognition system based on Gabor wavelet transform has been developed. Firstly, image coordinate system is defined to facilitate image alignment for feature extraction. Then, region of interest is cropped from the palmprint images. With developed system feature extracted of region of interest and given of k-NN classifier.Öğe Palmprint recognition system based on gabor wavelet transform with K-NN classifier model(INESEC, 2017) Çalışkan, Abidin; Ergen, Burhan; Acar, EmrullahPalmprint recognition system is regarded as reliable and accurate biometric identification system. The biometric approach palm recognition system has attracted the attention of researchers in recent times because of the presenting a new biometric feature compared to other models. In this work, gabor wavelet transform (GWT) based palmprint recognition system has been developed. Firstly, image coordinate system is determined in order to facilitate image alignment for feature extraction. Then, region of interest is cropped from the palmprint images. With the developed system, features are extracted from the region of interest and they are given to k-nearest neighbors (k-NN) classifier as input parameters. Finally, the highest success rate for GWT based systematic sampling was computed as 86.90% according to the non-request data selection and it was observed that the proposed recognition system provide successful results in classification of palmprint images. Moreover, a good identification of the feature vector is the main factor that affects performance. Thus, the performance can also be improved by finding more suitable feature vectors.Öğe Gabor dalgacık dönüşümü kullanarak avuç içi tanıma(IEEE, 2013-06-13) Çalışkan, Abidin; Ergen, BurhanAvuç içi tanıma sistemi, güvenilir ve doğru bir biyometrik tanıma sistemi olarak kabul edilir. Biyometrik yaklaşımlı avuç içi tanıma sistemi, diğer modellerle karşılaştırıldığında yeni bir biyometrik özellik olduğundan son zamanlarda araştırmacıların ilgisini çekmektedir. Bu çalışmada, Gabor dalgacık dönüşümü tabanlı avuç içi tanıma sistemi geliştirilmiştir. İlk olarak, özellik çıkarımın da görüntü uyumunu kolaylaştırmak için koordinat sistemi belirlenmiştir. Sonra, ilgilenilen bölge avuç içi imgesinden alınmıştır. Geliştirilen sistem ile ilgilenilen bölgenin özellikleri çıkartılmış ve Çok katmanlı algılayıcı sınıflandırıcısına verilmiştir.Öğe Fingerprint recognition system based on law’s texture energy measures with extreme learning machines(INESEC, 2017) Çalışkan, Abidin; Acar, Emrullah; Budak, CaferFingerprint recognition systems are one of the most popular biometric systems used in many areas, including prisons, border controls, educational institutions and forensic medicine. This paper presents a new approach based on the texture features for fingerprint recognition system. The dataset which employed in this study is obtained from the Hong Kong Polytechnic University High-ResolutionFingerprint database. The proposed system was implemented in two basic stages. Firstly, the texture feature vectors were extracted from the images by using Law’s Texture Energy Measures (TEM) and totally 9 parameters were extracted for each image as a feature vector. Then, the obtained feature vectors were classified by using Extreme Learning Machines (ELM) model. Finally, the average performance of the proposed system was computed according to different tuning parameters and the highest accuracy rate was observed as 83.92 % among the all system architectures.
