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Various Blocks of Canny Model
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... to design but sensitive to noise. Laplacian based edge detection techniques finds out derivative twice. A derivative mask acts like High Pass Filter. Thus, high frequency noise components can corrupt the whole image. A conventional Canny [3] By considering all three criteria mentioned above, Canny came up with a four block model (as shown in Fig. 1). The first block is used to eliminate high frequency noise. Generally, Gaussian filter is used here as a Low Pass Filter. Due to this, Canny often known as Gaussian of Gradient. In second block, any classical operator is used for gradient magnitude and orientation calculation. As Sobel is more efficient than Robert and Prewitt, ...
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Citations
... A. G. Mahalle et al. has proposed modified canny algorithm and implemented using Xilinx System Generator utilizes JTAG Hardware co-simulation approach. Spartan-3E FPGA is used as a reconfigurable hardware platform for the designed algorithm [1]. In computer vision, classical problem is determination of an optimal threshold automatically in edge detection. ...
... Experimentally, all spurious artifacts of a size less than 5% of the input image size are removed from the binary image. All image contours can then be found by using a modified canny edge detector [24] after erasing all irrelevant image components and isolated objects. The results in Figure 3 clearly show how the segmentation procedure allows for extremely accurate segmentation of skin lesions from the surrounding healthy skin regions. ...
Malignant melanoma is the most invasive skin cancer and is currently regarded as one of the deadliest disorders; however, it can be cured more successfully if detected and treated early. Recently, CAD (computer-aided diagnosis) systems have emerged as a powerful alternative tool for the automatic detection and categorization of skin lesions, such as malignant melanoma or benign nevus, in given dermoscopy images. In this paper, we propose an integrated CAD framework for rapid and accurate melanoma detection in dermoscopy images. Initially, an input dermoscopy image is pre-processed by using a median filter and bottom-hat filtering for noise reduction, artifact removal, and, thus, enhancing the image quality. After this, each skin lesion is described by an effective skin lesion descriptor with high discrimination and descriptiveness capabilities, which is constructed by calculating the HOG (Histogram of Oriented Gradient) and LBP (Local Binary Patterns) and their extensions. After feature selection, the lesion descriptors are fed into three supervised machine learning classification models, namely SVM (Support Vector Machine), kNN (k-Nearest Neighbors), and GAB (Gentle AdaBoost), to diagnostically classify melanocytic skin lesions into one of two diagnostic categories, melanoma or nevus. Experimental results achieved using 10-fold cross-validation on the publicly available MED-NODEE dermoscopy image dataset demonstrate that the proposed CAD framework performs either competitively or superiorly to several state-of-the-art methods with stronger training settings in relation to various diagnostic metrics, such as accuracy (94%), specificity (92%), and sensitivity (100%).
... Edge detection aims to identify points in an image at which the brightens or other image characteristics changes sharply. FPGAs' implementations for edge detection cover implementations based in Sobel operator [685][686][687][688][689], Canny algorithm [690][691][692], applications for real time processing [693][694][695][696][697], image segmentation [698,699], DNA (Desoxyribonucleic Acid) microarray image processing [700,701] and object detection [702][703][704] Digital watermarking is the act of hiding information in multimedia data, such as image, video or audio, for content protection or authentication [705]. FPGAs in digital watermarking have been used for real time watermarking detection in video [706,707], Discrete Cosine Transform (DCT) based digital image watermarking [708][709][710] and Discrete Wavelet Transform (DWT) based digital image/audio watermarking [555, 711,712]. ...
Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.
Image Enhancement is the process of improving the quality and the information content of original image so that resultant image becomes more suitable for display or further analysis. The main objective of image enhancement is to make image appropriate for the certain applications. Image enhancement techniques have been widely used in many applications of image processing where the subjective quality of images is important for human interpretation. Spatial domain refers to the image plane itself and is based on direct manipulation of pixels in an image. In this paper, various point processing and spatial filtering techniques are discussed in spatial domain. These techniques are implemented using reconfigurable hardware platform of field programmable gate array (FPGA). System Generator is used in order to integrate Xilinx FPGA design process with MATLAB/Simulink. It provides a high-level description to easily realize the complex computations of a digital image.
