image segmentation is a vital task in imageprocessing/computer vision. However, no universally accepted quality measure exists for evaluating the performance of various segmentation algorithms or even different param...
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ISBN:
(纸本)9781538618295
image segmentation is a vital task in imageprocessing/computer vision. However, no universally accepted quality measure exists for evaluating the performance of various segmentation algorithms or even different parameterizations of the same algorithm. This paper proposes a new segmentation evaluation measure, based on the fusion of HOG and Harris features, thus we call it the H2. It exploits local shape, corner and edge information to evaluate the similarity between a given segmentation and its respective ground truth, and thus belongs to the category of supervised evaluation measures. The results obtained from our experiments show accuracy of up to 95% for the H2.
A CNC(Computer Numerically Control) machine is a numerical control machine with the additional component of an on board PC. The PC is alluded to as the machine control unit(MCU).A novel mathematical model for the mach...
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ISBN:
(纸本)9781538604854
A CNC(Computer Numerically Control) machine is a numerical control machine with the additional component of an on board PC. The PC is alluded to as the machine control unit(MCU).A novel mathematical model for the machine tool feed derive system has been devised on MATLAB. A hardware model of solar powered three axes CNC machine is designed and fabricated which uses the input from the MATLAB. CNC machine model is designed using AUTOCAD and motor driving circuit is simulated and tested using *** UNO works as a controller to move the stepper motorsin x-, y-and z-axis. Before manufacturing of CNC machine. All imageprocessingalgorithms were designed and developed using MATLAB. The control unit is tested for linear and circular interpolation by performing actual machining on CNC machine. Here is an example of the image will be perceived as a SCET test using a CNC machine.
Decreasing size of CMOS technology plays a key role in embedding more and more functionalities in CMOS image sensors. By integrating sensing with processing, new types of CMOS imaging systems can be designed and appli...
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ISBN:
(纸本)9781509049912
Decreasing size of CMOS technology plays a key role in embedding more and more functionalities in CMOS image sensors. By integrating sensing with processing, new types of CMOS imaging systems can be designed and applied in domains such as machine vision, surveillance, or medical imaging. Digital pixel sensors (DPSs) are a good example of smart vision chips including image capturing and processing modules. Indeed, they incorporate, for each pixel, parallel analog-to-digital conversion thus allowing performing such conversion in early stages. Moreover, DPSs offer several benefits such as an improved SNR (Signal Noise Ratio) and a wider dynamic range. In addition, the emergence of new technologies, typically CMOS 3D-IC technology, offers the opportunity to reduce pixel area and improve fill factor, making DPSs suitable for numerous fields of applications. This paper presents a digital pixel sensor (DPS) integrating an in-pixel sigma-delta analog-to-digital converter (ADC). The digital pixel includes a photodiode, a delta-sigma modulation and a digital decimation filter, featuring high-speed conversion, programmable resolutions (up to 10-bit). Based on the CMOS 130 nm 3D-IC Tezzaron technology, an optimized design of the pixel is provided, revealing a high fill-factor of about 90%.
OCR (Optical Character Recognition) has been becoming a vital method to recognize digits, letters, symbols and so on. The main idea is basically the conversion of data files which consists of handwritten or machine-wr...
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ISBN:
(纸本)9781538670804;9788993215168
OCR (Optical Character Recognition) has been becoming a vital method to recognize digits, letters, symbols and so on. The main idea is basically the conversion of data files which consists of handwritten or machine-written digits or characters into a type to let the machine make edits and read. This way, it lets computers read articles or books. They can also read images and make the conversion to a text file by using OCR. There are two important benefits of OCR. First, is the enhancement of the device to operate more productively even if the number of employees is decreased. Secondly, is the increase in the efficiency of the storage. This paper compares two state-of-the-art OCR algorithms in a simulated environment by using modified dataset. Simulation results are shown in part 4.
Since the beginning of hand vein biometrics, the approaches to this problem have been countless, making this modality suitable for commercial use in some countries. This paper shows some of them and tries to show whic...
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ISBN:
(纸本)9781538615850
Since the beginning of hand vein biometrics, the approaches to this problem have been countless, making this modality suitable for commercial use in some countries. This paper shows some of them and tries to show which are the most common procedures in each of the main stages of these systems. We will be able to see that the same database usage is not common along the literature, being the main problem when evaluating the performance of a new system.
Interactive image segmentation is an important issue in computer vision. Many algorithms have been proposed for this problem. Among them, random walk based algorithms have been proved to be efficient. However, a large...
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ISBN:
(纸本)9783319700908;9783319700892
Interactive image segmentation is an important issue in computer vision. Many algorithms have been proposed for this problem. Among them, random walk based algorithms have been proved to be efficient. However, a large number of seeds (i.e., pixels with user-specified labels) must be given in advance to achieve a desirable segmentation for such algorithms, which makes user interaction inconvenient. To solve this problem, we improve the random walk algorithm in two aspects: (1) label prior is taken into account when computing edge weights between adjacent pixels;(2) each unseeded pixel is assigned with the same label as the seed with maximum first arrival probability to reduce the bias effect of seed size. The improved algorithm can achieve a desirable segmentation with few seeds. Experiment results on natural images illustrate the accuracy of the proposed algorithm.
This paper presents an application of a novel approach for detecting and tracking an object with a 2 DOF robotic manipulator which can be equipped with an array of electrically controlled actuators. The said approach ...
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ISBN:
(纸本)9788993215144
This paper presents an application of a novel approach for detecting and tracking an object with a 2 DOF robotic manipulator which can be equipped with an array of electrically controlled actuators. The said approach utilizes the image Based Visual Servoing (IBVS) technique. The developed system is able to determine the object pose in real time from features in the image. Object is detected using shaped based approach algorithms of imageprocessing. The position and orientation of the world coordinates of the object being tracked are calculated from the coordinates of the object in image plane using camera's intrinsic and extrinsic parameters. Experimental results demonstrate the effectiveness of this proposed approach.
Artifact elimination is a central issue in neurosciences. A method that has established itself as an important part of EEG analysis is the application of independent component analysis (ICA). It decomposes the multi-c...
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ISBN:
(纸本)9783319483085;9783319483078
Artifact elimination is a central issue in neurosciences. A method that has established itself as an important part of EEG analysis is the application of independent component analysis (ICA). It decomposes the multi-channel EEG into linearly independent components (ICs) that then can be classified as artifact or EEG signal component. However, classification of the ICs still requires visual, time-intensive inspection by experts. In order to develop an automated artifact elimination method, we apply several classification algorithms on feature vectors extracted from ICA components via imageprocessingalgorithms. We compare their performance with the ratings of experts and identify range filtering as a feature extraction method with great potential. Range images classified with artificial neuronal networks yield accuracy rates of 95.5%. The results are very promising regarding automated IC artifact recognition. Compared to existing automated solutions the proposed method has the main advantage that it is not limited to a specific number or type of artifact. Furthermore, it is an automatic, real-time capable, and practical tool that reduces the time-intensive manual selection of ICs for artifact removal.
The article presents a decision based algorithm of an automatic identification of markers in microscope images-ISH (In Situ Hybridization). The ISH test allows a quick and inexpensive initial diagnosis of the breast c...
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ISBN:
(纸本)9783319464909;9783319464893
The article presents a decision based algorithm of an automatic identification of markers in microscope images-ISH (In Situ Hybridization). The ISH test allows a quick and inexpensive initial diagnosis of the breast cancer. The evaluation of a degree of the HER2 gene's amplification and the selection of the appropriate treatment require locating and counting markers in cell nuclei. This article presents a new heterogeneous algorithm based on decision making. The main idea is to analyze a portion of an image and decide which algorithm should be used for processing the given fragment. The different parts of the image can be analyzed by different types of algorithms. Tests and results of the experiment are presented and discussed in this article. They confirm higher efficiency of markers recognition by the homogeneous system, using many different algorithms, rather than in the case of using the method based on a single algorithm.
Signatures are one of the important characteristics that security needs to be considered. Some cases related to signature forgery often occur, this is certainly dangerous especially if the signature forgery can be mis...
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ISBN:
(纸本)9781538670835;9781538670828
Signatures are one of the important characteristics that security needs to be considered. Some cases related to signature forgery often occur, this is certainly dangerous especially if the signature forgery can be misused. So there needs to be a verification process on the authenticity of signatures related to this. Several studies related to signature verification have been carried out, one of them using digital imageprocessing techniques. However, some studies only propose a method without comparison of results. This study aims to compare methods and development of signature verification methods based on digital imageprocessing with machine learning techniques. The final results of this research can later be used as a design module that can be used in system development or signature verification applications. The data used is the image of the digitization of the signature of the Lecturer in the STMIK AMIKOM Purwokerto environment. The segmentation method used in this study is adaptive maximum minimum thresholding with double morphological operation. Good segmentation results are expected to provide good classification results. Comparison of several different classifiers in the classification stage is carried out, including Linear Regression, Naïve Bayes (NB), Support Vector Machine (SVM), Multilayer Perceptron (MLP) and K-Nearest Neighbor (K-NN).
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