id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_a3hd5m5c6naslhdfexvsz5cxna	Humayan Kabir Rana	A fast iris recognition system through optimum feature extraction	2019	13	.pdf	application/pdf	4432	520	57	Keywords Biometrics, Iris Recognition, PCA, DWT, Gabor filter, Hough Transformation, of an iris and thereby reduce image resolution and in turn the runtime of the classification PCA + DWT and SVM are used for segmentation, normalization, feature extraction and classification respectively. Iris recognition processing generally consists of the following steps: (i) Image acquisition (ii) Iris segmentation (iii) Normalization (iv) Feature extraction and (v) Classification. A combined PCA and DWT were applied on a fixed size normalized iris for feature Once the circular iris region is successfully segmented from an eye image, normalization is DWT transforms normalized iris image into fourfrequency sub-bands, namely LL, LH, HL and HH. of classification time of two iris templates mostly depend on efficient feature extraction DWT transforms normalized iris image into LL sub-band represents the feature or characteristics of the iris (Acharya et al., 2017; Moni After applying DWT on a normalized iris image the resolution of	./cache/work_a3hd5m5c6naslhdfexvsz5cxna.pdf	./txt/work_a3hd5m5c6naslhdfexvsz5cxna.txt