The clustering technique is used to examine each pixel in the image which assigned to one of the clusters depending on the minimum distance to obtain primary classified image into different intensity regions. A waters...
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The clustering technique is used to examine each pixel in the image which assigned to one of the clusters depending on the minimum distance to obtain primary classified image into different intensity regions. A watershed transformation technique is then employes. This includes: gradient of the classified image, dividing the image into markers, checking the Marker image to see if it has zero points (watershed lines). The watershed lines are then deleted in the Marker image created by watershed algorithm. A Region Adjacency Graph (RAG) and Region Adjacency Boundary (RAB) are created between two regions from Marker image. Finally region merging is done according to region average intensity and two edge strengths (T1, T2). The approach of the authors is tested on remote sensing and brain MR medical images. The final segmentation result is one closed boundary per actual region in the image.
In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these i...
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In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.
Vehicle detection is one of the key technologies in Intelligent Transportation System (ITS), and it i an important stage of vehicle tracking in visual surveillance. Due to the clutter of traffic scenes, the captured v...
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The paper proposed a new method based on the multi-edited nearest neighbor rule to prevent decision tree algorithms from growing a tree of unnecessary large size and hence partially alleviate the problem of "over...
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Microscopic halftone imagerecognition and analysis can provide quantitative evidence for printing quality control and fault diagnosis of printing devices, while halftone image segmentation is one of the significant s...
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Microscopic halftone imagerecognition and analysis can provide quantitative evidence for printing quality control and fault diagnosis of printing devices, while halftone image segmentation is one of the significant steps during the procedure. Automatic segmentation on microscopic dots by the aid of the Fuzzy C-Means (FCM) method that takes account of the fuzziness of halftone image and utilizes its color information adequately is realized. Then some examples show the technique effective and simple with better performance of noise immunity than some usual methods. In addition, the segmentation results obtained by the FCM in different color spaces are compared, which indicates that the method using the FCM in the f1f2f3 color space is superior to the rest.
A circuit architechure to realize clock recovery for fast Ethernet applications is presented, whick includies system architecture, modified Mueller Muller algorithm for 100BASE-TX, phase detector for 100BASE-TX and mu...
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A circuit architechure to realize clock recovery for fast Ethernet applications is presented, whick includies system architecture, modified Mueller Muller algorithm for 100BASE-TX, phase detector for 100BASE-TX and multiple output charge pump PLL. The clock recovery circuit is verified by TSMC 0.35um 1P5M CMOS process. The results show that this clock recovery circuit exactly extracts the timing information. It has advantages over others for simple and easy implementation.
To meet the challenge of implementing rapidly advanced, time-consuming medical imageprocessing algorithms, it is necessary to develop a medical imageprocessing technology to process a 2D or 3D medical image dynamica...
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To meet the challenge of implementing rapidly advanced, time-consuming medical imageprocessing algorithms, it is necessary to develop a medical imageprocessing technology to process a 2D or 3D medical image dynamically on the web. But in a premier system, only static imageprocessing can be provided with the limitation of web technology. The development of Java and CORBA (common object request broker architecture) overcomes the shortcoming of the web static application and makes the dynamic processing of medical images on the web available. To develop an open solution of distributed computing, we integrate the Java, and web with the CORBA and present a web-based medical image dynamic processing methed, which adopts Java technology as the language to program application and components of the web and utilies the CORBA architecture to cope with heterogeneous property of a complex distributed system. The method also provides a platform-independent, transparent processing architecture to implement the advanced image routines and enable users to access large dataset and resources according to the requirements of medical applications. The experiment in this paper shows that the medical image dynamic processing method implemented on the web by using Java and the CORBA is feasible.
Automatic parameters selection is an important issue to make support vector machines (SVMs) practically useful. Most existing approaches use Newton method directly to compute the optimal parameters. They treat paramet...
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A major obstacle to the broader use of 3D object reconstruction and modeling is the extent of manual intervention needed. Such interventions are currently extensive and exist throughout every phase of a 3D reconstruct...
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Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Each vertex of a reduced graph corresponds to a connected set of vertices in the level below. One connected set of vertices ...
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