This paper introduces a linear in the parameter model for Homomorphic filter using Volterra series approach. To obtain these parameters we propose a model where we choose a sub image from the response of Homomorphic f...
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ISBN:
(纸本)9781509038183
This paper introduces a linear in the parameter model for Homomorphic filter using Volterra series approach. To obtain these parameters we propose a model where we choose a sub image from the response of Homomorphic filter as reference image to reduce computational complexity. We apply non uniform illuminated images to the proposed filter and compare its performance against standard Homomorphic filter. The proposed filter outperforms the traditional Homomorphic filter in all experiments. Also we compare the error convergence and steady-state error of Sparse aware LMS with LMS algorithm to calculate proposed filter coefficients.
This paper describes an efficient edge detection algorithm that can be used as a plug-in for digital imageprocessingsystems. The proposed algorithm uses a method based on iterative clustering targeting a reduced num...
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ISBN:
(纸本)9781509020478
This paper describes an efficient edge detection algorithm that can be used as a plug-in for digital imageprocessingsystems. The proposed algorithm uses a method based on iterative clustering targeting a reduced number of operations. The algorithm splits the image into two parts, background and foreground, and calculates the mean value for each of them. Based on these results, the new threshold value will be obtained and looped until the mean values remain unchanged. The only pixels affected by the change are the pixels with values between the previous two thresholds, so only they have to be redistributed to a new class. As a result, only few operations are needed in order to obtain the desired threshold. All the algorithms and results obtained in this paper are developed and tested using the C# programming language.
Emotion recognition systems have an important role to play in the human-computer interactive applications (HCI). These systems are using facial features of face images and they are verifying or identifying the emotion...
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ISBN:
(纸本)9781509016792
Emotion recognition systems have an important role to play in the human-computer interactive applications (HCI). These systems are using facial features of face images and they are verifying or identifying the emotions. In this study, emotion identification algorithms are improved by using just mouth region features of a face. Region of interest (mouth region) is detected by Viola-Jones algorithms from video frames which are including different emotional face expressions. Outer boundaries of lip shapes are extracted by manually and calculated the scalar Fourier Descriptors (FDs) of the boundaries. Classification and recognition of the emotions is presented according to scalar FDs of lip contours. Test results are obtained as 93.9 % accuracy rate for scalar FDs.
We are interested in building scalable computer vision systems for distributed processing of big visual data. We apply data streaming concepts, namely stream algebra operators, which have been proven effective in the ...
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ISBN:
(纸本)9781450347860
We are interested in building scalable computer vision systems for distributed processing of big visual data. We apply data streaming concepts, namely stream algebra operators, which have been proven effective in the database literature. The operators collectively form an algebra over data streams. The algebra has well defined semantics. It naturally describes online computer vision algorithms and their feedback control and tuning algorithms. In this work, we present the first implementation of such algebra at large scale. Our implementation provides a high level programming interface for constructing and executing vision workflow graphs while hiding the data transfer and concurrency details. It also allows feedback control and dynamic reconfiguration of vision algorithms. A case study is discussed showing a streaming workflow for online lane and road boundary detection and describing the flexibility and effectiveness of the algebra for building complex distributed applications.
Digital imageprocessing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its appl...
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ISBN:
(纸本)9781467384902
Digital imageprocessing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its applicability. The main objective of this paper is to demonstrate the ability of imageprocessingalgorithms on a small computing platform. Specifically we created a road sign recognition system based on an embedded system that reads and recognizes speed signs. The paper describes the characteristics of speed signs, requirements and difficulties behind implementing a real-time base system with embedded system, and how to deal with numbers using imageprocessing techniques based on shape and dimension analysis. The paper also shows the techniques used for classification and recognition. Color analysis also plays a specifically important role in many other different applications for road sign detection, this paper points to many problems regarding stability of color detection due to daylight conditions, so absence of color model can led a better solution. In this project lightweight techniques were mainly used due to limitation of real-time based application and Raspberry Pi capabilities. Raspberry Pi is the main target for the implementation, as it provides an interface between sensors, database, and imageprocessing results, while also performing functions to manipulate peripheral units (usb dongle, keyboard etc.).
This paper addresses the problem of assessing full-reference visual quality of images. A correlation between the obtained array of mean opinion scores (MOS) and the corresponding array of given metric values allows ch...
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Feature extraction (FE) is an efficient pre-processing step in hyperspectral image (HSI) classification. This article proposes a novel supervised FE method based on graph embedding framework (GEF). This method, which ...
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Feature extraction (FE) is an efficient pre-processing step in hyperspectral image (HSI) classification. This article proposes a novel supervised FE method based on graph embedding framework (GEF). This method, which is called marginal discriminant analysis using support vectors (MDSV), can be used as a linear dimensionality reduction approach. The proposed method constructs inner and support graphs to capture both global and local structures of data points. The global geometrical structure of data in each class is described by the inner graph. The support graph uses support vectors (SVs) to detect the local inter-class structure of different classes. Incorporating these graphs enables MDSV to maximize the margin between classes in the projected space. Implementation of MDSV on four benchmark hyperspectral datasets confirms its efficiency as an appropriate pre-processing method before classification of HSIs.
Purpose - The purpose of this paper is introducing the imageprocessing technology used for fabric analysis, which has the advantages of objective, digital and quick response. Design/methodology/approach - This paper ...
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Purpose - The purpose of this paper is introducing the imageprocessing technology used for fabric analysis, which has the advantages of objective, digital and quick response. Design/methodology/approach - This paper briefly describes the key process and module of some typical automatic recognition systems for fabric analysis presented by previous researchers;the related methods and algorithms used for the texture and pattern identification are also introduced. Findings - Compared with the traditional subjective method, the imageprocessing technology method has been proved to be rapid, accurate and reliable for quality control. Originality/value - The future trends and limitations in the field of weave pattern recognition for woven fabrics have been summarized at the end of this paper.
Target detection in hyperspectral images is important in many applications including search and rescue operations, defense systems, mineral exploration, mine detection and border security. In this study, the goal is t...
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ISBN:
(纸本)9781509016792
Target detection in hyperspectral images is important in many applications including search and rescue operations, defense systems, mineral exploration, mine detection and border security. In this study, the goal is to detect the nine sub-pixel targets, from seven different materials, that are placed around the town. For this purpose, eight hyperspectral target detection algorithms are compared and the three most successful algorithms are fused together. The results are compared with ROC curves, and it is found that the fusion of signed ACE, CEM and AMSD algorithms can achieve very successfull results in comparison to the other algorithms.
In recent years the growth in quantity, diversity and capability of Earth Observation (EO) satellites, has enabled increase's in the achievable payload data dimensionality and volume. However, the lack of equivale...
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ISBN:
(纸本)9781509018178
In recent years the growth in quantity, diversity and capability of Earth Observation (EO) satellites, has enabled increase's in the achievable payload data dimensionality and volume. However, the lack of equivalent advancement in downlink technology has resulted in the development of an onboard data bottleneck. This bottleneck must be alleviated in order for EO satellites to continue to efficiently provide high quality and increasing quantities of payload data. This research explores the selection and implementation of state-of-the-art multidimensional image compression algorithms and proposes a new onboard data processing architecture, to help alleviate the bottleneck and increase the data throughput of the platform. The proposed new system is based upon a backplane architecture to provide scalability with different satellite platform sizes and varying mission's objectives. The heterogeneous nature of the architecture allows benefits of both Field Programmable Gate Array (FPGA) and Graphical processing Unit (GPU) hardware to be leveraged for maximised data processing throughput.
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