Mustafa H. Mohammed Alhabib
Cihan University
Filter (signal processing)k-nearest neighbors algorithmSignalEuclidean distanceSupport vector machineBasis (linear algebra)Feature selectionArtificial intelligencePattern recognitionKernel Fisher discriminant analysisProjection (set theory)ThresholdingWavelet transformFace (geometry)Principal component analysisCauses of cancerPulse oximetryMammographyDigital mammographyScreening mammographyEarly Cancer DetectionImage basedAdaptive histogram equalizationFacial recognition systemComputer visionKernel (image processing)Computer scienceDigital imageLow-pass filterBreast cancerFast Fourier transformPulse (signal processing)Identification (information)Reduction (complexity)
Publications 4
This study examines the possibility of remotely measuring the cardiac pulse activity of a patient, which could be an alternative technique to the classical method. This type of measurement is non-invasive. However, several limitations may deteriorate the accuracy of the results, including changes in ambient illumination, motion artifacts (MA) and other interferences that may occur through video recording. The paper in hand presents a new approach as a remedy for the aforementioned problem in car...
Breast cancer remains one of the major causes of cancer deaths among women. For decades, screening mammography has been one of the most common methods for early cancer detection and diagnosis. Digital mammography images are created by applying a small burst of x-rays that pass through the breast to a solid-state detector, which transmits the electronic signals to a computer to form a digital image. However, due to projection, some mass areas may be partially covered, which makes them difficult t...
#1Mustafa H. Mohammed Alhabib (Cihan University)H-Index: 1
Last. Hussein Ibrahim Hussein (UniMAP: Universiti Malaysia Perlis)
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Facial analysis has evolved to be a process of considerable importance due to its consequence on the safety and security, either individually or generally on the society level, especially in personal identification. The paper in hand applies facial identification on a facial image dataset by examining partial facial images before allocating a set of distinctive characteristics to them. Extracting the desired features from the input image is achieved by means of wavelet transform. Principal compo...
Although many methods have been implemented in the past, face recognition is still an active field of research especially after the current increased interest in security. In this paper, a face recognition system using Kernel Discriminant Analysis (KDA) and Support Vector Machine (SVM) with K-nearest neighbor (KNN) methods is presented. The kernel discriminates analysis is applied for extracting features from input images. Furthermore, SVM and KNN are employed to classify the face image based on...
10 CitationsSource