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Chinese Optics Letters 2008年第12期6卷 886-888页

作者：牛海晶郭平宋晓东蒋田仔 image processing and pattern recognition Laboratory Beijing Normal University School of Computer Science and Technology Beijing Institute of Technology School of Aerospace Science and Engineering Beijing institute of Technology National Laboratory of pattern recognition institute of Automation Chinese Academy of Sciences

The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjustment method （EAM） based on maximum singular value of layered sensitivity is proposed. Optimal depth resolution can be achieved by compensating the reduced sensitivity in the deep medium. Simulations are performed using a semi-infinite model and the simulation results show that the EAM method can substantially improve the depth resolution of deeply embedded objects in the medium. Consequently, the image quality and the reconstruction accuracy for these objects have been largely improved.

关键词： Diagnostic radiography Electroabsorption modulators image quality Light absorption Medical imaging Optical tomography

Support Vector Regression Based Color image Restoration in YUV Color Space

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Journal of Shanghai Jiaotong university(Science) 2010年第1期15卷 31-35页

作者：黎明杨杰苏中义 institute of image processing and pattern recognition Shanghai Jiaotong University Department of Electronic Engineering Shanghai Dianji University

A support vector regression(SVR) based color image restoration algorithm is *** test color images are firstly mapped into the YUV color space,and then SVR is applied to build up a theoretical model between the degraded images and the original *** comparisons of the proposed algorithm versus traditional filtering algorithms are *** results show that the proposed algorithm has better performance than traditional filtering algorithms and has less computation time than iterative blind deconvolution algorithm.

关键词： color image restoration support vector regression (SVR) color space

Automatic segmentation of bladder in CT images

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第2期10卷 239-246页

作者： Feng SHI Jie YANG Yue-min ZHU institute of image processing and pattern recognition Shanghai Jiao Tong University Shanghai 200240 China CREATIS. LNSA of Lyon University of Lyon 1 Villeurbanne France

Segmentation of the bladder in computerized tomography(CT) images is an important step in radiation therapy planning of prostate cancer. We present a new segmentation scheme to automatically delineate the bladder contour in CT images with three major steps. First,we use the mean shift algorithm to obtain a clustered image containing the rough contour of the bladder,which is then extracted in the second step by applying a region-growing algorithm with the initial seed point selected from a line-by-line scanning process. The third step is to refine the bladder contour more accurately using the rolling-ball algorithm. These steps are then extended to segment the bladder volume in a slice-by-slice manner. The obtained results were compared to manual segmentation by radiation oncologists. The average values of sensitivity,specificity,positive predictive value,negative predictive value,and Hausdorff distance are 86.5%,96.3%,90.5%,96.5%,and 2.8 pixels,respectively. The results show that the bladder can be accurately segmented.

关键词： image segmentation Computerized tomography (CT) Mean shift Bladder Rolling ball

Liver fibrosis identification based on ultrasound images captured under varied imaging protocols

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2005年第11期6卷 1107-1114页

作者：曹桂涛施鹏飞胡兵 institute of image processing and pattern recognition Shanghai Jiao Tong University Department of Ultrasound in Medicine Shanghai Sixth Hospital Shanghai Jiao Tong University

Diagnostic ultrasound is a useful and noninvasive method in clinical medicine. Although due to its qualitative, sub- jective and experience-based nature, ultrasound image interpretation can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, Fisher linear classifier and support vector machine are employed to test a group of 99 in-vivo liver fibrosis images from 18 patients, as well as other 273 liver images from 18 normal human volunteers.

关键词： Liver fibrosis Texture Co-occurrence matrix Fisher classifier Support vector machine

Unsupervised Color-texture image Segmentation

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Journal of Shanghai Jiaotong university(Science) 2008年第1期13卷 71-75页

作者：郁生阳张艳王永刚杨杰 institute of image processing and pattern recognition Shanghai Jiaotong University Department of Computer Science Nanjing University of Science and Technology

The measure J in J value segmentation (JSEG) fails to represent the discontinuity of color, which degrades the robustness and discrimination of JSEG. An improved approach for JSEG algorithm was proposed for unsupervised color-texture image segmentation. The texture and photometric invariant edge information were combined, which results in a discriminative measure for color-texture homogeneity. Based on the image whose pixel values are values of the new measure, region growing-merging algorithm used in JSEG was then employed to segment the image. Finally, experiments on a variety of real color images demonstrate performance improvement due to the proposed method.

关键词： color-texture segmentation J value segmentation (JSEG) photometric color invariance edge detection region growing

A Closed Form Solution to Segment 3D Motion Using Straight-line Optical Flow

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Journal of Shanghai Jiaotong university(Science) 2008年第1期13卷 76-80页

作者：张婧石繁槐马文娟刘允才 institute image processing and pattern recognition Shanghai Jiaotong University School of Materials Science and Engineering Shanghai Jiaotong University

A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.

关键词： segmentation optical flow line generalized principal component analysis (GPCA)

New multi-camera calibration algorithm based on 1D objects

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2008年第6期9卷 799-806页

作者： Zi-jian ZHAO Yun-cai LIU institute of linage processing and pattern recognition Shanghai Jiao Tong University Shanghai 200240 China

A new calibration algorithm for multi-camera systems using 1D calibration objects is proposed. The algorithm inte- grates the rank-4 factorization with Zhang (2004)'s method. The intrinsic parameters as well as the extrinsic parameters are re- covered by capturing with cameras the 1D object's rotations around a fixed point. The algorithm is based on factorization of the scaled measurement matrix, the projective depth of which is estimated in an analytical equation instead of a recursive form. For more than three points on a 1D object, the approach of our algorithm is to extend the scaled measurement matrix. The obtained parameters are finally refined through the maximum likelihood inference. Simulations and experiments with real images verify that the proposed technique achieves a good trade-off between the intrinsic and extrinsic camera parameters.

关键词： Multi-camera calibration Homography Factorization Scaled measurement matrix Projective depth

image matching navigation based on fuzzy information

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Journal of Harbin institute of Technology(New Series) 2003年第4期10卷 447-449页

作者：田玉龙吴伟仁田金文柳健 State Key Laboratory for image processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

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.

关键词： image matching fuzzy information similarity

Hardware Implementation and System Control Strategy of Videoconference System Based on Rec. H. 261

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High Technology Letters 1995年第2期1卷 73-77页

作者：闫安 institute of image processing & pattern recognition Shanghai Jiao Tong University Shanghai 200030 P. R. China

The design and realization of a videoconference system based on international recommendation are introduced in this paper, and the hardware implementation of video codec based on ITU-T H. 261 is briefly discussed. Furthermore, the buffer control method and the adaptive control strategy for quantization are proposed, which are adaptive and robust. This system can be operated under the transmission rate ranging from 128kb/s to 2Mb/s. With these strategies for the videoconference system, the high quality image is obtained. The time delay of the system is about half a second.

关键词： Recommendation H. 261 Videoconference Codec Buffer control

Real-time instance segmentation based on contour learning

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Journal of Measurement Science and instrumentation 2024年第3期15卷 328-337页

作者： GE Rui LIU Dengfeng ZHOU Haojie CHAI Zhilei WU Qin School of Artificial Intelligence and Computer Science Jiangnan UniversityWuxi 214122China Jiangsu Provincial Engineering Laboratory pattern recognition and Computational Intelligence Jiangnan UniversityWuxi 214122China

instance segmentation plays an important role in image *** Deep Snake algorithm based on contour iteration deforms an initial bounding box to an instance contour end-to-end,which can improve the performance of instance segmentation,but has defects such as slow segmentation speed and sub-optimal initial *** solve these problems,a real-time instance segmentation algorithm based on contour learning was ***,ShuffleNet V2 was used as backbone network,and the receptive field of the model was expanded by using a 5×5 convolution ***,a lightweight up-sampling module,multi-stage aggregation(MSA),performs residual fusion of multi-layer features,which not only improves segmentation speed,but also extracts effective features more ***,a contour initialization method for network learning was designed,and a global contour feature aggregation mechanism was used to return a coarse contour,which solves the problem of excessive error between manually initialized contour and real ***,the Snake deformation module was used to iteratively optimize the coarse contour to obtain the final instance *** experimental results showed that the proposed method improved the instance segmentation accuracy on semantic boundaries dataset(SBD),Cityscapes and Kins datasets,and the average precision reached 55.8 on the SBD;Compared with Deep Snake,the model parameters were reduced by 87.2%,calculation amount was reduced by 78.3%,and segmentation speed reached 39.8 frame·s−1 when instance segmentation was performed on an image with a size of 512×512 pixels on a 2080Ti *** proposed method can reduce resource consumption,realize instance segmentation tasks quickly and accurately,and therefore is more suitable for embedded platforms with limited resources.

关键词： instance segmentation ShuffleNet V2 lightweight network contour initialization