In this paper, an integral design that combines optical system with imageprocessing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often...
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ISBN:
(纸本)9781510601154
In this paper, an integral design that combines optical system with imageprocessing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of imageprocessingalgorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for imageprocessing. In conclusion. The integral design of optical system and imageprocessing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.
Retinal image Quality Assessment (RIQA) is an essential preliminarily step in Automatic Retinal Screening systems (ARSS) to avoid misdiagnosis of retinal disease. In this work, a no-reference wavelet based RIQA algori...
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While object detection is a relatively well-developed field with respect to visible light photographs, there are significantly fewer algorithms designed to work with other imaging modalities. X-ray radiographs have ma...
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ISBN:
(数字)9781510603301
ISBN:
(纸本)9781510603295;9781510603301
While object detection is a relatively well-developed field with respect to visible light photographs, there are significantly fewer algorithms designed to work with other imaging modalities. X-ray radiographs have many unique characteristics that introduce additional challenges that can cause common imageprocessing and object detection algorithms to begin to fail. Examples of these problematic attributes include the fact that radiographs are only represented in gray scale with similar textures and that transmission overlap occurs when multiple objects are overlaid on top of each other. In this paper we not only analyze the effectiveness of common object detection techniques as applied to our specific database, but also outline how we combined various techniques to improve overall performance. While significant strides have been made towards developing a robust object detection algorithm for use with the given database, it is still a work in progress. Further research will be needed in order to deal with the specific obstacles posed by radiographs and X-ray imaging systems. Success in this project would have disruptive repercussions in fields ranging from medical imaging to manufacturing quality assurance and national security.
The aim of Content-based image Retrieval (CBIR) is to find a set of images that best match the query based on visual features. Most existing CBIR systems find similar images in low level features, while Text-based Ima...
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ISBN:
(纸本)9783319466729;9783319466712
The aim of Content-based image Retrieval (CBIR) is to find a set of images that best match the query based on visual features. Most existing CBIR systems find similar images in low level features, while Text-based image Retrieval (TBIR) systems find images with relevant tags regardless of contents in the images. Generally, people are more interested in images with similarity both in contours and high-level concepts. Therefore, we propose a new strategy called Deep Search to meet this requirement. It mines knowledge from the similar images of original queries, in order to compensate for the missing information in feature extraction process. To evaluate the performance of Deep Search approach, we apply this method to three different CBIR systems (HOF [5], HOG and GIST) in our experiments. The results show that Deep Search greatly improves the performance of original algorithms, and is not restricted to any particular methods.
High resolution and high throughput imaging are typically mutually exclusive. While there is a wide range of techniques to image features beyond the diffraction limit of light, they all have their own benefits and dra...
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ISBN:
(纸本)9781509060009
High resolution and high throughput imaging are typically mutually exclusive. While there is a wide range of techniques to image features beyond the diffraction limit of light, they all have their own benefits and drawbacks, but they are often very slow compared to optical systems. As such, extending the performance of optical microscopes remains. Examples of high resolution optical concepts are metamaterials nano-antennas, superoscillatory lenses and hyperlenses. These concepts require precise and high speed positioning of the optical element at lens-to-sample separations measured in tens of nanometers. We present a design and process for a MEMS nanopositioning stage capable of sub-nm positioning of a metamaterials optical lens with very high bandwidth. Laser vibrometer measurements on the first batch of fully fabricated devices showed that the first eigenfrequency is at 500 +/- 25 kHz, somewhat below the 660 kHz obtained by FEM simulations. Due to squeeze film damping, the quality factor is relatively low (approximately 2-2.5), which is advantageous for reaching high positioning bandwidth when the device is used in a near-field optical imaging microscope.
This paper presents an efficient image denoising method by incorporating shearlet-based histogram thresholding. Nowadays, digital images are used in wide range of applications but most of these images are degraded dur...
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In this digital world, accurate text identification and recognition has become an important key area of image document analysis and processing. Textual data, ranging from simple to complex images along with language v...
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ISBN:
(纸本)9781467378079
In this digital world, accurate text identification and recognition has become an important key area of image document analysis and processing. Textual data, ranging from simple to complex images along with language variations - mono, bi, tri or multilingual scripts, is identified and extracted. This paper is designed to focus the challenges and complex issues of text recognition in bilingual machine printed imaged documents. Major crucial factors are discovered and mentioned which become the bottlenecks in correct and accurate recognition. With this, a hierarchical structure depicting three Classification Schemes (CS) A, B and C of bilingual printed imaged document is shown, where A, B and C are related to the content form, image mining and language or script determination. Some loopholes of OCR working are also discussed. To analyze the existing algorithms and methods, a survey is presented to focus on their critical issues, proposed solutions along with constraints and errors found during text processing. It leads to find out the shortcomings and limitations of different methods. Various specifications and factors found from the techniques are also shown as their characteristics and are compared relatively to distinguish them. It is observed that most of the existing methods are based on the classification schemes CS A-Al and C-Cl and C2 and are designed for the script identification with 300 dpi gray scale image using SVM classifier.
The article describes parallel implementations of two parametric identification algorithms. The first algorithm is based on the estimation of Bravais unit cell parameters, and the second one estimates Wigner-Seitz cel...
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The article describes parallel implementations of two parametric identification algorithms. The first algorithm is based on the estimation of Bravais unit cell parameters, and the second one estimates Wigner-Seitz cell volumes. The developed parallel implementations are based on the two-tier model of concurrency. An external tier of concurrency uses Message Passing Interface (MPI) technique to distribute parametric identification tasks between computing nodes. An internal tier uses Open Multi-processing (OpenMP) technique to split single steps of the parametric identification algorithms into independent subtasks. Experimental results on multi-processor/multi-core systems have demonstrated almost linear speedup of the parallel implementations, confirmed the effectiveness of the two-tier concurrency model and proved the stability of the identification approach under lattice distortion.
The two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca,. Morelos, Mexico, in October *** total of 98 pap...
ISBN:
(纸本)9783319271002
The two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca,. Morelos, Mexico, in October *** total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; imageprocessing and computer vision; search and optimization; forecasting; and intelligent applications.
This paper addresses the problem of using live and pre-recorded video sources in 3D reconstruction systems. Typical photogrammetry packages use images generated from digital photography cameras such as DSLRs. 3D recon...
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ISBN:
(纸本)9781509020508
This paper addresses the problem of using live and pre-recorded video sources in 3D reconstruction systems. Typical photogrammetry packages use images generated from digital photography cameras such as DSLRs. 3D reconstruction algorithms require the intrinsic information to be stored in the EXIF header of a digital photograph. Live video systems don't store this information and more importantly don't produce a concise sequence of distinct frames. This paper presents an approach to using both live and pre-recorded video sources with 3D Structure from Motion systems through the implementation of a pre-processor. This approach filters the video feed with the aid of the Laplacian operator and feature-based methods to create an optimal sequence for both on-line and off-line 3D reconstruction systems.
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