Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on FVC2004 databases that have a four database; every database is eighty fingers and eight impressions per finger. The implemented recognition results of the proposed system show high recognition performance which is 100%.
Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image
... Show MoreIn this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .
in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators
In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
Due to the difficulties that Iraqi students face when writing in the English language, this preliminary study aimed to improve students' writing skills by using online platforms remotely. Sixty first-year students from Al-Furat Al–Awsat Technical University participated in this study. Through these platforms, the researchers relied on stimuli, such as images, icons, and short titles to allow for deeper and more accurate participations. Data were collected through corrections, observations, and feedback from the researchers and peers. In addition, two pre and post-tests were conducted. The quantitative data were analysed by SPSS statistical Editor, whereas the qualitative data were analyzed using the Piot table, an Excel sheet. The resu
... Show MoreDigital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.
First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .
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