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In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For tr...
Interactive segmentation, in which a user provides a bounding box to an object of interest for image segmenta-tion, has been applied to a variety of applications in im-age editing, crowdsourcing, comp...
Mammographic density is an important risk factor for breast cancer, detecting and screening at an early stage could help save lives. To analyze breast density distribution, a good segmentation algorit...
This thesis presents a Field Programmable Gate Array (FPGA) based embedded system which is used to achieve high speed segmentation of 3D images. Segmenta- tion is performed using Expectation-Maximizat...
In this thesis, 3D image segmentation is targeted to a Xilinx Field Programmable Gate Array (FPGA), and verified with extensive simulation. Segmentation is performed using the Expectation-Maximization...
We address the task of unsupervised topic segmentation of speech data operating over raw acoustic information. In contrast to existing algorithms for topic segmentation of speech, our approach does no...
General object recognition and image understanding is recognized as a dramatic goal for computervision and multimedia retrieval. In spite of the great e®orts devoted in the last two decades, it s...
Segmenting hair regions from human images facilitates many tasks like hair synthesis and hair style trends forecast. However, hair segmentation is quite challenging due to hair/background confusion an...
In this paper, we propose a novel method toevaluate table segmentation results based on a table imageground truther. In the ground-truthing process, we first extractconnected components from agi...
提出一种利用核模糊C均值聚类(KFCM)和改进分水岭算法分割猪肉眼肌切面图像中背最长肌区域的方法。该算法对经中值滤波去噪后图像的R分量利用最大方差自适应阈值(OTSU)去除背景,再采用KFCM提取出肌肉组织,然后进行空洞填充,最后由改进的分水岭算法分割出背最长肌区域。利用该算法对采集的60幅猪肉眼肌图像进行处理,分割正确率为86.67%;与传统的形态学算法相比,该算法能真实、完整地恢复出背最长肌区...
In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior probabilities (HOPP) with...
为了解决K-均值算法对农业图像中常用的超绿特征2G—R—B图像分割效果不佳的缺点,提出一种基于微粒群与K均值算法的图像分割方法。先用K均值算法对图像进行快速分类,然后将分类结果作为其中一个微粒的结果,利用微粒群算法计算,最后用K-均值算法在新的分类基础上计算新的聚类中心,更新当前的位置,以得到最优的图像分割阈值。试验结果表明,改进算法对超绿特征2G—R—B图像能够准确分割目标,且对不同类型的农业超...
In this paper, we present a hybrid text segmentation approach for embedded text in images, aiming to combining the advantages of the difference-based methods and the similarity-based methods together....
通过直方图分析,建立了适用于棉花异性纤维图像的增强模型;提出了改进Otsu法,并对Otsu方法的分割效果进行了深入分析。实验结果表明,所有棉花异性纤维图像的灰度直方图基本都呈单峰特性;所建的增强模型可以显著提高异性纤维目标与皮棉背景之间的对比度;改进Otsu法将最佳阈值的搜索范围从0~255缩减到150~230,使此环节的计算速度提高了2倍多。
Text segmentation, or named text binarization, is usually an essential step for text information extraction from images and videos. However, most existing text segmentation methods have difficulties i...

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