The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm has been developed for clustering purpose. Mainly, the purpose of using modified K-means clustering technique is to group the similar features into (K) templates in order to simulate the differences in the ways that human express each emotion. To evaluate the proposed system, a subset from Cohen-Kanade (CK) dataset have been used, it consists of 870 facial images samples for the seven basic emotions (angry, disgust, fear, happy, normal, sad, and surprise). The conducted test results indicated that SVM classifier can lead to higher performance in comparison with the results of other proposed methods due to its desirable characteristics (such as large-margin separation, good generalization performance, etc.).
A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.
Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a
... Show MoreComputer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc
... Show MoreThe importance of the current study lies in the importance of the Tax policy that being considered one of the most important tools working on fulfilling the social, financial and economic goals and improving the investment environment in the country to become having the ability to activate the national economy. The current study has referred that ( Has the tax planning practiced by the Iraqi contribution companies led to increase the far-term tax outcome through getting benefit of the monetary funds and expansion in&nbs
... Show MoreA total of 41 patients with gastro duodenal symptoms (show signs of inflammation with or without duodenal ulcer) . 21 males (51.2%) and 20 female (48.8%) with an average age 0f (20 – 80) years old under going gastrointestinal endoscopy at Baghdad teaching hospital in internal disease clinical laboratory , between (February – June) 2009 . Biopsies specimen of antrum , gastric fundus ,& duodenal bulb were examined by the following methods (rapid urease test , Giemsa stain section to detect bacteria , & Haematoxilin and Eosin stained section for pathological study which are considered the gold standard methods , sera or plasma from these patients were tested by immunochromotography (ICM),serological m
... Show MoreIn this paper, we made comparison among different parametric ,nonparametric and semiparametric estimators for partial linear regression model users parametric represented by ols and nonparametric methods represented by cubic smoothing spline estimator and Nadaraya-Watson estimator, we study three nonparametric regression models and samples sizes n=40,60,100,variances used σ2=0.5,1,1.5 the results for the first model show that N.W estimator for partial linear regression model(PLM) is the best followed the cubic smoothing spline estimator for (PLM),and the results of the second and the third model show that the best estimator is C.S.S.followed by N.W estimator for (PLM) ,the
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