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).
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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ISBN:
(纸本)9781509033508
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 during transmission and acquisition process. Removal of noise from images is still a challenging task for many researchers because there is always a trade-off between noise removal and fine edge preservation. This paper is based on image denoising using shearlet transform. Shearlets have excellent features for data analysis and processing, which overcomes the limitation of traditional methods. They are optimally sparse and have multi-scale and multi-directional properties which are optimal in representing image containing edges. In this paper, the proposed method is found to produce superior peak signal-to-noise ratio (PSNR) over the conventional denoising algorithms.
Estimator algorithms rely on assumed laser stripe image profile to determine its peek with sub-pixel accuracy. They depend on light intensity readings around the peak and are susceptible to noise and saturation. Noise...
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ISBN:
(纸本)9781509018987
Estimator algorithms rely on assumed laser stripe image profile to determine its peek with sub-pixel accuracy. They depend on light intensity readings around the peak and are susceptible to noise and saturation. Noise and stripe intensity models are commonly used to synthesize and feed test data to estimator algorithms in order to evaluate their accuracy and robustness. For real-time 3D scanning applications estimator algorithms are expected to prefer less computationally demanding estimation techniques. Simple and accurate models of empirical noise and laser stripe profile could be used to improve testing and algorithms accuracy. Modular test setup for 3D scanning is utilized to project a laser stripe on the target with patterned surface. Laser stripe image is captured and processed to extract noise and surface pattern interference. Laser power modulation is used to generate series of captures with various stripe intensities. Captures are partitioned, analyzed and presented according to target surface properties and color channels. image noise interfering with sub-pixel peak detection is analyzed and noise model based on empirical data is proposed. Empirical laser stripe images are analyzed and novel simple laser stripe intensity profile model conforming to empirical data is proposed.
In this paper, we propose a novel scheme for image restoration (IR) employing a sequential decoding technique based on a tree search, known as Stack algorithm. The latter is a well-known method used for ID signal deco...
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ISBN:
(纸本)9781509018918
In this paper, we propose a novel scheme for image restoration (IR) employing a sequential decoding technique based on a tree search, known as Stack algorithm. The latter is a well-known method used for ID signal decoding in wireless communication systems. The main idea is to extend the Stack algorithm for image restoration (2D) and to exploit the information diversity conveyed by the channels (Multichannel) in order to restore the original image. To deal with the noisy case, a regularization term is introduced using the total variation and the wavelet transform. This method was tested on artificially degraded images (blurred and noisy). Obtained results confirm the relevance of the proposed approach.
The edge detection is one of the key techniques in most imageprocessing applications. The canny edge detection is proven to be able to significantly outperform existing edge detection techniques due to its superior p...
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The edge detection is one of the key techniques in most imageprocessing applications. The canny edge detection is proven to be able to significantly outperform existing edge detection techniques due to its superior performance. Unfortunately, the implementation of the systems in real-time is computationally complex, high hardware cost with increased latency. The proposed canny edge detection algorithm uses approximation methods to replace the complex operations, the pipelining is employed to reduce the latency. Finally, this algorithm is implemented on Xilinx Virtex-5 FPGA. When compared with the previous hardware architecture for canny edge detection, the proposed architecture requires fewer hardware costs and takes 1ms to detect the edges of 512×512 image.
Segmentation is a process to obtain the desirable features in imageprocessing. However, the existing techniques that use the multilevel thresholding method in image segmentation are computationally demanding due to t...
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ISBN:
(纸本)9781467378086
Segmentation is a process to obtain the desirable features in imageprocessing. However, the existing techniques that use the multilevel thresholding method in image segmentation are computationally demanding due to the lack of an automatic parameter selection process. This paper proposes an automatic parameter selection technique called an automatic multilevel thresholding algorithm using stratified sampling and Tabu Search (AMTSSTS) to remedy the limitations. It automatically determines the appropriate threshold number and values by (1) dividing an image into even strata (blocks) to extract samples; (2) applying a Tabu Search-based optimization technique on these samples to maximize the ratios of their means and variances; (3)preliminarily determining the threshold number and values based on the optimized samples; and (4) further optimizing these samples using a novel local criterion function that combines with the property of local continuity of an image. Experiments on Berkeley datasets show that AMTSSTS is an efficient and effective technique which can provide smoother results than several developed methods in recent years.
Many computer role-playing games that mime a science fiction or fantastic world have a static world map or the map changes under some scripted assumptions that hardly reproduce the dynamic of a play. In this paper I p...
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ISBN:
(纸本)9781509041251
Many computer role-playing games that mime a science fiction or fantastic world have a static world map or the map changes under some scripted assumptions that hardly reproduce the dynamic of a play. In this paper I propose a novel algorithm that enables real time terrain calculation even on a very large world map. An algorithm uses approach based on attraction force calculation and uses gradient methods combined with fast approximation of Gaussian filter and fast implementation of median filtration. With such an approach it is possible to fast adapt and rebuild the virtual world taking into account every nuance that happened during play. Due to this a player has the feeling of control and influence of his or her deeds to overall game which is very important aspect of every role-playing scenario. Because single iteration of an algorithm last about 176.01 ± 12.57 milliseconds (in frequency nearly 6 Hz for large 256×256 grids) the resulting map might be adjusted dynamically during game and a player might be aware of it. This size of a grid is sufficient for simulation very large virtual world that typically appears in role-playing games.
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