The structure of the brain can be seen by the Magnetic Resonance (MR) image output. MR scanned image of the brain is utilized for the entire study in this paper. The MR image filter is more agreeable than some other o...
详细信息
ISBN:
(纸本)9781538623695
The structure of the brain can be seen by the Magnetic Resonance (MR) image output. MR scanned image of the brain is utilized for the entire study in this paper. The MR image filter is more agreeable than some other outputs for analysis. It will not influence the human body since it does not hone any radiation. In digitization of MR scanned image, segmentation of brain tumor is one kind of challenging problems and it is critical to clinical diagnosis. So segmentation needs to be accurate, robust, and efficient to avoid impacts caused by various large and complex biases added to images. Clustering algorithms have been widely used for the segmentation. In this paper, the K-means (KM) clustering and Fuzzy C-means (FCM) clustering algorithms are used to locate the tumor and extract it. Comparative analysis in terms of Segmented area, Relative area, Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) is performed between K-means clustering and FCM clustering algorithms. The obtained performance measures from the experiments indicate the superiority of the chosen FCM algorithm over the K-means algorithm. That is 0.93% of relative segmented tumor area for FCM shows that the area which was effected by the tumor in the original MR image is segmented as a tumor. The FCM Algorithm has less processing time of 8.639 seconds compared to 22.831 seconds for KM algorithm.
Style transfer is an increasingly popular field that can capture the styles of a particular artwork and use them to synthesize a new image with specific content. Previous NST algorithms have the limitation to transfer...
详细信息
Quality criteria are the essence of a measurement system. The goal of assessing the quality of software elements (algorithms) used for imageprocessing is to ensure control of technical performance indicators of the s...
Quality criteria are the essence of a measurement system. The goal of assessing the quality of software elements (algorithms) used for imageprocessing is to ensure control of technical performance indicators of the system as a whole or its individual functional units under the reduction of costs associated with minimizing the loss function (tuning and debugging). The correct choice of individual metrics for the generalized quality indicator to solve tasks in a particular subject area is one of the key steps in system optimization. It ensures the most flexible approach to testing the developed software elements, identifying and eliminating their functional shortcomings. At the same time, we can say that in this way the generalized indicator of the entire system (its goal function) is optimized.
One of the most common uses of FPGAs is as implementation platforms for graphics processing applications. Their structure can exploit spatial and temporal parallelism, but such parallelisation depends on the processin...
详细信息
ISBN:
(纸本)9781538647882
One of the most common uses of FPGAs is as implementation platforms for graphics processing applications. Their structure can exploit spatial and temporal parallelism, but such parallelisation depends on the processing model and hardware constraints of the system. Those restrictions can force the designer to reformulate the algorithm. In this paper we present an FPGA design as a portable USB accelerator device which implements the Grayscale and Sobel Edge Detection algorithms, two of the most fundamental algorithms in digital imageprocessing.
Testing using the co-simulation method of an algorithm is important to visualize the hardware performance of the algorithm. This study aims to introduce a method for comparing the hardware performance of two different...
详细信息
ISBN:
(纸本)9781538656020
Testing using the co-simulation method of an algorithm is important to visualize the hardware performance of the algorithm. This study aims to introduce a method for comparing the hardware performance of two different algorithms with a focus on the existing compression system for capsule endoscopy as a case study. The size limitation of capsule endoscopy which constrains the power source and the complexity of the hardware utilization are the main reasons for selecting the capsule endoscopy compression system for this case study. Undertaking a comparison between different algorithms from the existing image compression algorithms in capsule endoscopy can highlight the main testing steps of the co-simulation testing method. To allow a fair comparison, the hardware co-simulation is implemented using the same FPGA device for the methods compared in this study and the results acquired are discussed.
Pitch extraction is a well-known and prominent application in signal processing. However, there are chances for improvements yet. This paper proposes a methodology based on laryngeal mechanisms background for pitch ex...
详细信息
ISBN:
(纸本)9781538669792
Pitch extraction is a well-known and prominent application in signal processing. However, there are chances for improvements yet. This paper proposes a methodology based on laryngeal mechanisms background for pitch extraction. The goal is to optimize the frequency range of the pitch detectors relying on the fact that each laryngeal mechanism has a frequency range, and therefore, it is not necessary to use all range of human voice to every sound, since it was produced in just one specific mechanism. Since our proposal consists of parameter tuning, it is not limited to specific pitch extraction algorithms. Our experiments show that this adjustment on the frequency range can significantly improve pitch detection accuracy.
With increasing urbanization, waste has become a major problem in the present world. Therefore, proper waste management is a must for a healthy and clean environment. Though government authorities in most countries pr...
详细信息
ISBN:
(数字)9781728184128
ISBN:
(纸本)9781728184135
With increasing urbanization, waste has become a major problem in the present world. Therefore, proper waste management is a must for a healthy and clean environment. Though government authorities in most countries provide various solutions for waste management, solid waste tends to make a significant impact on the environment as they do not decompose easily. This research focuses on AI (Artificial Intelligence)-driven smart waste bin that can classify the most widely available solid waste materials namely Metal, Glass, and Plastic. The smart waste bin performs the separation of waste using imageprocessing and machine learning algorithms. The system also performs the continuous monitoring of the collected waste level by using ultrasonic sensors. A dedicated mobile application will generate the optimal routes for the available waste collectors to collect the filled bins. Moreover, with this smart bin, the challenge of recognizing each waste item is overcome by using visual data as the source. Therefore, the usage of expensive sensor devices and filtration techniques to determine the category is disregarded. The smart bin can recognize the category of solid waste, collect it to the specified container, and notify the garbage level in each container. So, it is a portable waste management system.
image registration and photo-mosaicing of related imagery from unmanned aerial vehicles (UAVs) is an active research topic. Aerial photography and mosaicing became crucial for surveillance and reconnaissance. It consi...
详细信息
ISBN:
(纸本)9781538669792
image registration and photo-mosaicing of related imagery from unmanned aerial vehicles (UAVs) is an active research topic. Aerial photography and mosaicing became crucial for surveillance and reconnaissance. It consists in aligning multiple images to construct a single large image of a 3D scene allowing the operator to view images that offers a wider field of view than standard images. Offline registration and mosaicing of collected images from UAVs has proven to give great results but is numerically intensive and somewhat slow. In this paper, a new approach for real time mosaicing is proposed based on new registration approach which reduces accumulated error and distortion of the current image. A quantitative analysis of the new approach is performed. This analysis allows the comparison of two images mosaic using some parameters to evaluate the quality, the Distortion rate and the speed of mosaicing.
In this paper, we proposed an algorithm based on game theory for document image binarization. For designing the algorithm, we formulate document image binarization using zero-sum game in which foreground of the image ...
详细信息
ISBN:
(数字)9781728153506
ISBN:
(纸本)9781728153513
In this paper, we proposed an algorithm based on game theory for document image binarization. For designing the algorithm, we formulate document image binarization using zero-sum game in which foreground of the image with textual shapes and background of the image are considered as two players. Then the best distance between the players is calculated. Finally, a global threshold is set for binarization of the image. The proposed algorithm is called Zero-sum image Binarization Algorithm (ZIBA). The experimental results show that ZIBA has admissible precision for document image binarization.
Dynamic speckle is an interferometric phenomenon, which has been considered a sensitive way to monitor the weak changes in biological samples, and therefore it is a reliable tool that can be applied in many areas, fro...
详细信息
暂无评论