Description: In this work, a new approach to fully automatic color
image segmentation, called JSEG, is presented. First, colors
in the image are quantized to several representing
classes that can be used to differentiate regions in the
image. Then, image pixel colors are replaced by their corresponding
color class labels, thus forming a class-map of
the image. A criterion for “good” segmentation using this
class-map is proposed. Applying the criterion to local windows
in the class-map results in the “J-image”, in which
high and low values correspond to possible region boundaries
and region centers, respectively. A region growing
method is then used to segment the image based on the
multi-scale J-images. Experiments show that JSEG provides
good segmentation results on a variety of images. Platform: |
Size: 4101120 |
Author:artjuna |
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Description: 段扫描，实现二值图像连通区域的标记，该算法运算速度快，优于递归算法。-Segment scanning, binary image connected region marked, the algorithm is fast, better than the recursive algorithm. Platform: |
Size: 1024 |
Author:joanna |
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Description: 对一副图像进行区域增长分割，有中文注释，易于学习-To segment a image by using region growing, with Chinese annotation, easy to learn
Platform: |
Size: 36864 |
Author:疾风 |
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Description: 通过提取图像上某一区域的颜色信息,程序能图像上所有与该区域具有相同颜色的其他区域分割出来。-Through extracting color image information of an area , program can segment all the other regions which have the same color as the extracted region. segmentation.
Platform: |
Size: 3072 |
Author:匡红立 |
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Description: susan的理论知识
如图1所示，图片是白色背景，有一个颜色比较暗淡的矩形。在图片上有5个圆形区域。圆形区域表示的是掩码区域。把圆形区域内的每一个位置的像素值与圆心处的像素值相比较，那么圆中的的像素可以分为两类，一类是像素值与圆心处的像素值相近的，另一类是像素值与圆心的处的像素值相差比较大的。那么，把第一类（像素值与圆心处的像素值相近的）所组成的区域称为USAN，USAN的全称是“Univalue Segment Assimilating Nucleus”。图2 中显示了图1中的5个圆的USAN区域。图2中，圆中的白色区域是表示该掩码区域的USAN区域。
USAN区域表征了图像局部结构的信息，对USAN的区域的大小及二阶矩的分析，可以得到图像中的角点，边缘等信息-susan theoretical knowledge in Figure 1, the background image is white, there is a color in dim rectangle. On the image there five circular area. A circular area represents the area of the mask. The circular area of each position and the center pixel value compared to the value at the pixel, then the circle of the pixels can be divided into two categories, one is at the center pixel value and the pixel values are similar, and the other is the pixel value of the pixel values at the center of the relatively large difference. So, the first category (the center pixel value and the pixel values at similar) consisting of area is called USAN, USAN' s full name is " Univalue Segment Assimilating Nucleus" . Figure 2 shows the Figure 1 USAN circle area 5. Figure 2, the circle represents the white area is the area of the mask region USAN. USAN area characterizes the local structure of the image informat Platform: |
Size: 1138688 |
Author:贺家乐 |
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Description: 提出一种基于特征点的运动场景图像拼接算法。基于相似变换消除选取在运动物体上的特征点，并使用RANSAC算法进行外点的剔除。在融合阶段，根据齐次变换矩阵求得对2幅图像的差异图像，并执行区域增长算法。从而分割出运动区域。使用一种分段映射算法生成全景图像。实验证明了算法的有效性。-A feature-based algorithm for image mosaics of 8c宅Iles with moving objects is pI．oposcd．The algorithm eliminates the feature points which arc selected in
moving objects using similarity transform，and the outliers are eliminated using RANSAC algorithm．In
the image blend phase，a difference of two images is created using homogeneous transformation matrix，and a region growth algorithm is implemented SO as to segment the movmg object region．A piecewise mapping algorithm for generating panoramic images is used．Experimental results show the effectiveness of the algorithm． Platform: |
Size: 329728 |
Author:紫烟 |
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Description: 图像匹配是图像处理的基本问题，同时也一个难点，本代码是基于直线描述子的场景匹配。-Line segment matching plays an important role in image processing and computer vision, while it remains a challenging task for images under various transformations. In this work, we present a line matching algorithm which considers both the local appearance of lines and their geometric attributes. To overcome the problem of segment fragmentation and geometric variation, we extract lines in the scale space. To depict the local appearance of lines, we design a novel line descriptor called as Line Band Descriptor (LBD) based on the band representation of the Line Support Region (LSR). To uate the pairwise geometric consistencies, we define the pairwise geometric attributes between line pairs. Then we built a relational graph for candidate line matches and employ a spectral technique to solve this matching problem efficiently. The advantages of the proposed algorithm are as follows: (1) it s robust to image transformations because of the multi-scale line detection strategy (2) it s effic Platform: |
Size: 2534400 |
Author:hitxrb |
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Description: This code mainly for image enhancement. Here we are apply seeded region growing to segment foreground and background. And enhance the foreground part alone using. Finally we combined the foreground and background part. Code very suitable for medical images which have low resolution. Platform: |
Size: 449536 |
Author:vasanth |
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Description: 利用K均把图片分割成3部分。无需注明基点。-use adaptive K means to segment an image into 3 region without the need to specify cluster number. Platform: |
Size: 2048 |
Author:yihui |
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Description: 加快K均把图片分割成3部分。cluster number 已被固定。-K means clustering algorithms with faster response to segment an image into specific 3 region Platform: |
Size: 2048 |
Author:yihui |
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Description: 使用形态学操作把细胞分割成关注区.图片会经过扩张，侵蚀已填铺细胞空洞-use morphology operation to segment in cell image into region of ROI Platform: |
Size: 1024 |
Author:yihui |
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Description: image analysis, since thickening of the bladder wall
can indicate abnormality. However, it is a challenging task due to
the artifacts inside bladder lumen, weak boundaries in the apex
and base areas, and complicated outside intensity distributions.
To deal with these difficulties, in this paper, an adaptive shape
prior constrained directional level set model is proposed to segment
the inner and outer boundaries of the bladder wall. In addition,
a coupled directional level set model is presented to refine
the segmentation by exploiting the prior knowledge of region information
and minimum thickness. With our proposed method,
the influence of the artifacts in the bladder lumen and the complicated
outside tissues surrounding the bladder can be appreciably
reduced Platform: |
Size: 1906688 |
Author:yangs |
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Description: 提出了一种分散、递阶蚁群算法, 它将多个分散的蚁群并行求解各自对应的子问题, 形成一个执行层, 而递阶协调层利用执行层反馈的信息协调执行层的优化过程,从而得到递阶求解问题的整体最优解. 该算法已应用于相变热图序列图像模糊相变线的提取问题,即运用区域划分方法先将序列图像的分割转化为关联型多子图搜索问题,再利用分散 、递阶蚁群算法进行求解 ,结果表明该算法能很好地利用相变线的运动信息成功地解决热相变序列图像分割问题. 与蚁群算法独立搜索比较 ,分散 、递阶蚁群算法能更有效地实现多子图之间的关联.(A class of decentralized and hierarchical ant colony optimization is presented , in which the sub- problem is solved by multiple decentralized ant colonies side by side to form an execute level. The optimization process of the execute level is coordinated in the hierarchical coordination level with the feedback information from the execute level to obtain the general optimal solution of the hierarchical solving pro blem. The algorithm is applied to the extraction problem of fuzzy phase change lines of phase change thermograph sequences , where the sequences image segment is transformed into search problems of associated multiple sub- images by region partition method, then solved by decentralized and hierarchical ant colony algorithm. The simulation results show that the moving information of phase change lines can be utilized well to solve the segment problem of phase change thermograph by the proposed algorithm.) Platform: |
Size: 513024 |
Author:Janet1023
|
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