A knowledge-based fuzzy clustering (KBFC) MRI segmentation algorithm was proposed to obtain accurate tumor segmentation for tumor volume measurement of nasopharyngeal carcinoma (NPC). An initial segmentation was perfo...
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ISBN:
(纸本)0819444294
A knowledge-based fuzzy clustering (KBFC) MRI segmentation algorithm was proposed to obtain accurate tumor segmentation for tumor volume measurement of nasopharyngeal carcinoma (NPC). An initial segmentation was performed on T1 and contrast enhanced T1 MR images using a semi-supervised fuzzy c-means (SFCM) algorithm. Then, three types of anatomic and space knowledge-symmetry, connectivity and cluster center were used for image analysis which contributed the final tumor segmentation. After the segmentation, tumor volume was obtained by multi-planimetry method. visual and quantitative validations were performed on phantom model and six data volumes of NPC patients, compared with ground truth (GT) and the results acquired using seeds growing (SG) for tumor segmentation. In visual format, KBFC showed better tumor segmentation image than SG. In quantitative segmentation quality estimation, on phantom model, the matching percent (MP) / correspondence ratio (CR) was 94.1-96.4% / 0.8880.925 for KBFC and 94.1-96.0% / 0.884-0.918 for SG while on patient data volumes, it was 92.1+/-2.6% / 0.884+/-0.014 for KBFC and 87.4+/-4.3% / 0.843+/-0.041 for SG. In tumor volume measurement, on phantom model, measurement error was 4.2-5.0% for KBFC and 4.8-6.1% for SG while on patient data volumes, it was 6.6+/-3.5% for KBFC and 8.8+/-5.4% for SG. Based on these results, KBFC could provide high quality of MRI tumor segmentation for tumor volume measurement of NPC.
A fuzzy hybrid filter (FHF) is presented which can remove impulse noise from highly corrupted images while preserving details. Primarily noise ratio in the filter window, is defined and detected. Then we present new d...
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ISBN:
(纸本)0780374908
A fuzzy hybrid filter (FHF) is presented which can remove impulse noise from highly corrupted images while preserving details. Primarily noise ratio in the filter window, is defined and detected. Then we present new detection algorithm of corrupted degree of central pixel in the filter window, and fuzzy decision based on fuzzy rules, construct the fuzzy membership function. Finally fuzzy hybrid filter (FHF) is designed for the removal of impulse noise from highly corrupted images. Experimental results indicate that our algorithm impressively outperforms other techniques in terms of noise suppression and detail preservation across a wide range of impulse noise corruption, ranging from 5% to 80%. Moreover the FHF can effectively restore images corrupted with mixed Gaussian and impulse noise.
By using integer discrete cosine transform (IntDCT) based on lifting steps, we in this paper introduce an integer hierarchy lapped biorthogonal transform via lifting steps called the IntHLBT. When all elements with fl...
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We present sampling results for certain classes of 2-D signals that are not bandlimited, but have a parametric representation with a finite number of degrees of freedom, such as 2-D Diracs, polygons and bilevel signal...
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ISBN:
(纸本)0780374029
We present sampling results for certain classes of 2-D signals that are not bandlimited, but have a parametric representation with a finite number of degrees of freedom, such as 2-D Diracs, polygons and bilevel signals with piecewise polynomial boundaries. As opposed to standard multidimensional sampling schemes, the proposed methods exploit the properties of the Radon transform of such signals. In particular, we demonstrate that by using an appropriate sampling kernel, one can perfectly reconstruct the signal from a finite set of samples of its Radon transform, and thus significantly reduce a computational load. The novel approach we present in the paper, offers practical algorithmic implementation and is potentially applicable to a large class of two-dimensional signals.
In this paper, we deal with the colour naming visual task in computer vision. Our goal is to develop a colour naming model to be included in a real surveillance application, where images have to be automatically annot...
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ISBN:
(纸本)0892082399
In this paper, we deal with the colour naming visual task in computer vision. Our goal is to develop a colour naming model to be included in a real surveillance application, where images have to be automatically annotated with people clothes description, for a further content-based image browsing. Although colour naming has been a usual goal in psychophysical. research, it is a quite novel topic in computer vision. Colour naming is posed as a fuzzy set problem where each colour category is presented as a fuzzy set with a characteristic function. Our goal is to find a model which provides membership values as similar as possible to the values that would give a real observer. To this end, we propose a Sigmoid-Gaussian model as the membership function of the colour fuzzy categories. We analyse its properties and results to confirm the suitability of this model versus most common Gaussian models. To test the results, we have developed a colour naming experiment that has provided a set of membership values for a set of colour samples. Although the data used is far from being a complete learning set, it has been a first step to evaluate the proposed model.
OFDM modulation, which has been adopted by the Digital Video Broadcasting (DVB-T) standard in Europe, has been recognized for its good performance for high data rate wireless communications. Therefore, the study of th...
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OFDM modulation, which has been adopted by the Digital Video Broadcasting (DVB-T) standard in Europe, has been recognized for its good performance for high data rate wireless communications. Therefore, the study of the robust transmission of multimedia data over the OFDM systems has attracted extensive research interest. In the past, channel estimation, which is an important aspect in OFDM systems, has not been exploited for multimedia transmission. When using the block-training based channel estimation schemes, there exists a periodic variation of the error rates due to the channel estimation imprecision. We use this property to provide unequal error protection (UEP) for the video transmission. Compared with systems using pilot-training based channel estimation schemes, which are recommended in the DVB-T standard, a performance gain of about 2dB in the PSNR of the reconstructed images is achieved.
The US Army's Future Combat Systems (FCS) and Objective Force will rely heavily on the use of unattended sensor net-works to detect, locate and identify enemy targets in order to survive with less armor protection...
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ISBN:
(纸本)0819444936
The US Army's Future Combat Systems (FCS) and Objective Force will rely heavily on the use of unattended sensor net-works to detect, locate and identify enemy targets in order to survive with less armor protection on the future battlefield. Successful implementation of these critical communication net-works will require the collection of the sensor data, processing and collating it with available intelligence, then transporting it in a format conducive to make quick and accurate command decisions based on the latest tactical situational awareness. The networked communications must support both static deployed and mobile ground and air robotic sensors with secure, stealthy, andjam resistant links for sensor fusion and command and control. It is envisioned for broadest application that sensor networks can be deployed in a two-tiered architecture. The architecture includes a lower sensor sub-layer consisting of mixes of acoustic, magnetic and seismic detectors and an upper sub-layer consisting of infrared or visualimagers. The upper sub-layer can be cued by the lower sub-layer and provides a gateway link to the higher echelon tactical maneuver layer networks such as the Tactical Internet. The sensor deployments, networking constraints and reach back distances to Command and Control (C2) nodes will be mission scenario specific, however, the architecture will also apply to tactical unattended sensor, munition and robotic applications. Technologies from the Army Research Laboratory, Defense Advance Research Projects Agency (DARPA), and commercial will be leveraged for this effort.
This paper describes algorithms. to extract features of facial organs such as eyes, eyebrows, mouth, nose and borders of other parts. Based on these extracted organs, automatic face drawing is generated, which embodie...
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ISBN:
(纸本)0780374886
This paper describes algorithms. to extract features of facial organs such as eyes, eyebrows, mouth, nose and borders of other parts. Based on these extracted organs, automatic face drawing is generated, which embodies the individual features that the face looks more likely to be so. At first face detection is implemented by using horizontal textures and eigenfaces.. After that, the pair of irises re located using Hough-transform and intensity valley correlation. Then other organs are extracted based on the skeleton characteristic of the face. For face drawing generating, contours are rendered with multi-values, facial skin color is smoothed, and features are strengthened. in order to get impressive effects.
In recent years, there has been a huge growth in the areas of multimedia and wireless communications. image transmission through bandwidth limited and high bit error rate wireless channel requires both compression and...
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In recent years, there has been a huge growth in the areas of multimedia and wireless communications. image transmission through bandwidth limited and high bit error rate wireless channel requires both compression and error resilient capabilities. We propose an error resilient image coding and smart error concealment schemes for DCT-based image compression, such as JPEG and MPEG standards. It can successfully prevent error propagation between the transmitted data blocks with little overhead. In addition, we present a novel post-processing error concealment scheme, called Smart-IDCT (SIDCT). It tries to retain error free low frequency DCT information and discarding highly suspicious high frequency information. Then, we can retrieve low-resolution information instead of totally corrupted image block during the decoding process. The required computation power is much less than conventional error detection and correction schemes. Simulation results show that the overhead of ERIC is about 5% compared to the JPEG sequential DCT-based mode without restart marker. With the SIDCT post-processing, it can achieve excellent image quality (PSNR=31.78dB).
Realtime rendering of scenes with discrete levels of detail (LOD) often suffers from noticeable visual changes between succesive frames. We propose geomorphing to obtain smoother animations while retaining guaranteed ...
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ISBN:
(纸本)9781581136081
Realtime rendering of scenes with discrete levels of detail (LOD) often suffers from noticeable visual changes between succesive frames. We propose geomorphing to obtain smoother animations while retaining guaranteed frame rates. Our level of detail management calculates a set of representations, that are well suited for some future time interval according to the predicted motion of the user. Thus, the rendering system has enough time to change the representations smoothly to the desired level of detail. Further on uniprocessor systems, the time used by the LOD selection is amortized between several frames.
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