This paper briefly describes and evaluates SICOS, a tool for Social image Cluster-based Organization and Search, allowing to group together images sharing similar semantic and visual features, to simplify their organi...
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ISBN:
(纸本)9781509052820
This paper briefly describes and evaluates SICOS, a tool for Social image Cluster-based Organization and Search, allowing to group together images sharing similar semantic and visual features, to simplify their organization and querying following user preferences. The system consists of modular components for: i) feature extraction and representation (low-level and high-level), ii) partitional image clustering (initial clustering phase executed when the user first connects to the system), iii) incremental clustering (updating clusters produces in the previous phase by processing newly published images), iv) fast image querying (using features of cluster representatives), and v) personalized images and search results visualization (using various user-chosen cluster display techniques). Experiments highlight the efficiency of the tool.
Some of the imageprocessingalgorithms are verycostly in terms of operations and time. To use these algorithmsin real-time environment, optimization and vectorization arenecessary. In this paper, approaches are propo...
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ISBN:
(纸本)9781467382878
Some of the imageprocessingalgorithms are verycostly in terms of operations and time. To use these algorithmsin real-time environment, optimization and vectorization arenecessary. In this paper, approaches are proposed to optimize, vectorize and how to fit the algorithm in low memory space. Here, optimized anisotropic diffusion based fog removal algorithm isproposed. Fog removal algorithm removes the fog from imageand produces an image having better visibility. This algorithmhas many phases like anisotropic diffusion, histogram stretchingand smoothing. Anisotropic diffusion is an iterative process thattakes nearly 70% of time complexity of the whole algorithm. Here, optimization and vectorization of the anisotropic diffusion is proposed for better performance. However, optimizationtechniques cost some accuracy but that can be neglected forsignificant improvement in performance. For memory constraintenvironment, a method is proposed to process the entire blockof image and maintains the integrity of operations. Resultsconfirm that with our optimization and vectorization approaches, performance is increased up to 90 fps (approximately) for VGAimage on one of the imageprocessing DSP simulator. Even if, system doesn't have vector operations, the proposed optimizationtechniques can be used to achieve better performance (2× faster).
This paper presents the implementation of an adaptive contour detection filter and tumor Characterization on field programmable gate array (FPGA) using a combination of hardware and software components. The proposed s...
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This paper presents the implementation of an adaptive contour detection filter and tumor Characterization on field programmable gate array (FPGA) using a combination of hardware and software components. The proposed system locates contours from a calculation of Gradient in preferred directions while quantifying the importance of the outline with a wise thresholding. The dedicated algorithm is implemented in an FPGA Xilinx Spartan 6, and results are displayed in a VGA monitor. The FPGA offers the necessary performance for imageprocessing and video in real time, while maintaining the flexibility of the system to support an adaptive algorithm. Simulation results and synthesis proposed edge detection processor on FPGA chip demonstrate the efficiency of proposed architecture.
Thinning is an important pre-processing step in many shape based character and word recognition systems. The one-pixel wide thinned character image is useful for identifying the shape of various strokes used to from t...
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ISBN:
(纸本)9781467399401
Thinning is an important pre-processing step in many shape based character and word recognition systems. The one-pixel wide thinned character image is useful for identifying the shape of various strokes used to from the character, which is helpful in many applications such as word spotting in the document image, content-based document image retrieval, character and word classification, etc. However, all thinning algorithms generate unwanted spurious edges. As a result, the shape of the stroke is distorted which in turn limits the accuracy of stroke recognition in characters. Thus, removal of these spurious edges from thinned image will improve the state of the art in stroke recognition and benefit many applications stated above. This paper presents a survey of various techniques used for removal of spurious edges from thinned character image and tries to identify the challenges and research gaps in the problem.
An imaging flow cytometer based on Fourier sampling is demonstrated to enable high throughput screening with a frame rate of 625 kHz and a throughput of 100,000 cells/s for the first time.
ISBN:
(纸本)9781509019076
An imaging flow cytometer based on Fourier sampling is demonstrated to enable high throughput screening with a frame rate of 625 kHz and a throughput of 100,000 cells/s for the first time.
This paper proposes a new haze-removal scheme for automotive applications. In contrast that the previous works focus on enhancing the quality of haze-free images, the proposed algorithm sharpens the edges of lanes by ...
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ISBN:
(纸本)9781509032204
This paper proposes a new haze-removal scheme for automotive applications. In contrast that the previous works focus on enhancing the quality of haze-free images, the proposed algorithm sharpens the edges of lanes by adopting the weighting filter. Moreover, the previous internal steps, which cannot improve the sharpness of lanes, are removed to reduce the computing overheads. As a result, the proposed haze-removal algorithm improves the sharpness of lanes remarkably, while providing the real-time imageprocessing for advanced driver assistance systems.
Digital imageprocessing is versatile study in this era. Many researchers implement different types of association like image restoration, enhancement and segmentation etc. Implementing image-processingsystems can en...
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ISBN:
(纸本)9781467399159
Digital imageprocessing is versatile study in this era. Many researchers implement different types of association like image restoration, enhancement and segmentation etc. Implementing image-processingsystems can entail considerable attempt and assets due to information volume and algorithm complexity. Input image including noise, reduction or removal of noise is one form of image enhancement. This anticipated endeavor deal with creating an optimized image analysis environment with three states such as Noise Reduction, Edge Detection and Segmentation. This effort involves creating a new modeling representation for compare the performance using various filters in these three states. In this paper, detailed comparative study of noise removal filters, edge detection techniques and segmentation techniques are analyzed and compared the performances.
Tape and reel packaging process is one of the important final manufacturing process of electric chip. During and after this packaging process, the defects of chips in the tape and reel package should be inspected. It ...
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ISBN:
(纸本)9781467390583
Tape and reel packaging process is one of the important final manufacturing process of electric chip. During and after this packaging process, the defects of chips in the tape and reel package should be inspected. It is so time and cost consuming task by human inspectors. The main defects of chip in the tape and reel package are orientation chip, a wrong type chip and marking defects of chips. In this paper, the automatic vision system and imageprocessingalgorithms are developed to inspect the above defects on tape and reel packaging process. The high speed vision algorithm is based on multi-thread and parallel processing method to meet the inspection time(minimum 200 chips/min). Experiments were performed to evaluate the proposed vision inspection algorithms. The experimental result shows that our algorithm achieves high accuracy and speed for industrial requirement.
Lane Detection (LD) systems are now commonly used in autonomous cars to assist drivers. However, LD takes up only a small part of the Advanced Driver Assistant systems (ADAS) and should be highly optimised to make mor...
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ISBN:
(纸本)9781509018185
Lane Detection (LD) systems are now commonly used in autonomous cars to assist drivers. However, LD takes up only a small part of the Advanced Driver Assistant systems (ADAS) and should be highly optimised to make more room for other more complicated algorithms such as stereo vision systems that are incorporated into an ADAS. This paper mainly focuses on an optimised implementation of the linear lane detection system based on multiple image pre-processing methods and an efficient Hough transform (HT). To evaluate the performance of the algorithm, it was implemented on the TMS320C6678 System on Chip (SoC) Digital Signal Processor (DSP). The proposed algorithm is programmed in C language, which is compatible across multiple platforms especially for DSP to achieve a much faster performance than real-time. In order to reduce the noise in the HT accumulator and decrease the processing time, a Gaussian blur, edge thinning and border suppression were used. These gave not only an increase of 92.8% in performance but also a detection rate increase of 33.7%. To enhance the performance further and make use of all the cores of the SoC, the complete system has been implemented with Open Multi-processing (OpenMP). This gave a further increase of 76.7% when an appropriate load distribution was used. On the implementation side, the accumulator size was reduced by around 35.5% which is an important factor for an embedded system. Experimental results showed that the system achieved a high performance of 81 fps on images with the resolution of 1242 by 375.
processing of synthetic aperture radar (SAR) images has led to the development of SAR image despeckling approaches. These approaches help to suppress the Speckle in SAR image. In this paper, we propose a Synthetic Ape...
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ISBN:
(纸本)9781509025534
processing of synthetic aperture radar (SAR) images has led to the development of SAR image despeckling approaches. These approaches help to suppress the Speckle in SAR image. In this paper, we propose a Synthetic Aperture Radar (SAR) image despeckling method based on patch ordering and transform domain filtering. The proposed method consists of two-stage filtering strategy. The first stage is coarse filtering. In this stage, denoising is done by simultaneous Sparse Coding (SSC). The second stage is refined filtering which can eliminate small artifacts generated by the coarse filtering. In this stage, filtered image is obtained by Wavelet Hard thresholding. Experimental results with both denoised images and SAR images demonstrate that the proposed method achieves state-of-art despeckling performance in terms of Structural Similarity Index Measure (SSIM), Peak Signalto-Noise Ratio (PSNR).
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