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.).
In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny
... Show MoreFace recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima
... Show MoreAim of the study: Is to evaluate the effect of myrrh oil local application on the healing process of skin wounds histologically , histomorphometrically and , histochemically. Materials and methods:Twenty male white New Zealand rabbits were used in this study. An incisional wounds with full thickness depth and of 2 cm length were done on both sides of the cheek skin of each rabbit. The left sided incisions (the control group) were irrigated with distilled water (10µL). The right sided incisions (the experimental groups) were treated with myrrh oil (10µL). Each group was subdivided into 4 subgroups according to the healing interval into 1,3,7 and 14 days(5 rabbits for each group). Results: Histological findings of our current study s
... Show MoreBackground: The success and maintenance of indirect dental restorations is closely related to the marginal accuracy, which is affected by many factors like preparation design, using of different fabrication techniques, and the time of taking final impression and pouring it. The purpose of this in vitro study was to evaluate the effect of different pouring time of conventional impression on the vertical marginal gap of full contour zirconia crowns in comparison with digital impression technique. Materials and Methods: Forty sound recently extracted human permanent maxillary first premolar teeth of comparable size and shape were collected. Standardized preparation of all teeth samples were carried out to receive full contour zirconia crown re
... Show MoreBackground: The success and maintenance of indirect dental restorations is closely related to the marginal accuracy, which is affected by many factors like preparation design, using of different fabrication techniques, and the time of taking final impression and pouring it. The purpose of this in vitro study was to evaluate the effect of different pouring time of conventional impression on the vertical marginal gap of full contour zirconia crowns in comparison with digital impression technique. Materials and Methods: Forty sound recently extracted human permanent maxillary first premolar teeth of comparable size and shape were collected. Standardized preparation of all teeth samples were carried out to receive full contour zirconia crown re
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreThere is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into
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