Object detection and tracking is one of the most researched areas in computer vision and is recei... more Object detection and tracking is one of the most researched areas in computer vision and is receiving a growing attention because of its wide area of applications which include surveillance, industrial inspection, robotics, mobiles, and 3D gaming among others. This paper focuses and presents the implementation of Speed Up Robust Feature in development of a Detection and Tracking System for inanimate objects. The system can detect an inanimate object from a still image containing many other objects which have been saved as data set as well as detect and track objects using webcam. The algorithm is developed in Microsoft Visual Basic 2010 express edition using Speed Up Robust Feature available in EmguCV libraries which are used for the image processing and computer vision tasks. A Logitech C310 High Definition webcam with 5 Mega Pixel is used for the purpose of real-time detection and tracking. Keywords— Object detection, tracking; EmguCV; Speed Up Robust Feature (SURF); Images
Signal & Image Processing : An International Journal, 2012
In computer vision, segmentation refers to the process of partitioning a digital image into multi... more In computer vision, segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). This paper attempts to undertake a study of two categories of image segmentation which are Contour-Base and Region-Base. In the first category, Contour-Based image segmentation, the study is on some edge detection techniques which include Sobel, Canny and Robert Cross edge detection techniques and for the Region-based image segmentation, the study is on image thresholding. These two categories of image segmentation will be performed using MATLAB Version 7.12.0.635 (R2011a) and the experimental results obtained are discussed.
In computer vision, segmentation refers to the process of partitioning a digital image into multi... more In computer vision, segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). This paper attempts to undertake a study of two categories of image segmentation which are Contour- Base and Region-Base. In the first category, Contour- Based image segmentation, the study is on some edge detection techniques which include Sobel, Canny and Robert Cross edge detection techniques and for the Region- based image segmentation, the study is on image thresholding. These two categories of image segmentation will be performed using MATLAB Version 7.12.0.635 (R2011a) and the experimental results obtained are discussed.
Object detection and tracking is one of the most researched areas in computer vision and is recei... more Object detection and tracking is one of the most researched areas in computer vision and is receiving a growing attention because of its wide area of applications which include surveillance, industrial inspection, robotics, mobiles, and 3D gaming among others. This paper focuses and presents the implementation of Speed Up Robust Feature in development of a Detection and Tracking System for inanimate objects. The system can detect an inanimate object from a still image containing many other objects which have been saved as data set as well as detect and track objects using webcam. The algorithm is developed in Microsoft Visual Basic 2010 express edition using Speed Up Robust Feature available in EmguCV libraries which are used for the image processing and computer vision tasks. A Logitech C310 High Definition webcam with 5 Mega Pixel is used for the purpose of real-time detection and tracking. Keywords— Object detection, tracking; EmguCV; Speed Up Robust Feature (SURF); Images
Signal & Image Processing : An International Journal, 2012
In computer vision, segmentation refers to the process of partitioning a digital image into multi... more In computer vision, segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). This paper attempts to undertake a study of two categories of image segmentation which are Contour-Base and Region-Base. In the first category, Contour-Based image segmentation, the study is on some edge detection techniques which include Sobel, Canny and Robert Cross edge detection techniques and for the Region-based image segmentation, the study is on image thresholding. These two categories of image segmentation will be performed using MATLAB Version 7.12.0.635 (R2011a) and the experimental results obtained are discussed.
In computer vision, segmentation refers to the process of partitioning a digital image into multi... more In computer vision, segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). This paper attempts to undertake a study of two categories of image segmentation which are Contour- Base and Region-Base. In the first category, Contour- Based image segmentation, the study is on some edge detection techniques which include Sobel, Canny and Robert Cross edge detection techniques and for the Region- based image segmentation, the study is on image thresholding. These two categories of image segmentation will be performed using MATLAB Version 7.12.0.635 (R2011a) and the experimental results obtained are discussed.
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Papers by Fari Abubakar