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    • 6. 发明授权
    • 라벨 영역 분할방법
    • 标签区域分类方法
    • KR101215569B1
    • 2012-12-26
    • KR1020110146589
    • 2011-12-29
    • 전남대학교산학협력단
    • 진연연박상철나인섭김수형
    • G06K7/10G06K9/20
    • G06K9/50G06K9/6202G06T7/12
    • PURPOSE: A label area division method is provided to enable a user to receive or purchase a product including a label by recognizing a label area from an input image. CONSTITUTION: An importance area creation unit creates a predetermined area of an input image as an importance area(S1000). A vertical edge detection unit detects two vertical edges from the importance area and creates an area which is covered with the vertical edges as a label candidate area(S2000). A label area encoding unit creates encoded label area code by calculating the similarity of a direction and a size between pixels in a boundary of the label candidate area(S4000). A label area separation unit separates an area matched with the label area code from the input image(S5000). [Reference numerals] (S1000) Creating an importance area; (S2000) Creating vertical edges and a label candidate area which is covered by the vertical edges; (S3000) Detecting horizontal edges which cross with vertical edges; (S4000) Creating a label area code connected to vertical edges and horizontal edges; (S5000) Dividing a label area matching with a label code area in an inputted image
    • 目的:提供一种标签区域分割方法,以使用户能够通过从输入图像中识别标签区域来接收或购买包括标签的产品。 构成:重要区域创建单元创建输入图像的预定区域作为重要区域(S1000)。 垂直边缘检测单元从重要性区域检测两个垂直边缘,并创建被垂直边缘覆盖的区域作为标签候选区域(S2000)。 标签区域编码单元通过计算标签候选区域的边界中的方向和像素之间的大小的相似度来创建编码标签区域代码(S4000)。 标签区域分离单元将与标签区域代码匹配的区域与输入图像分离(S5000)。 (S1000)创建重要区域; (S2000)创建垂直边缘和由垂直边缘覆盖的标签候选区域; (S3000)检测与垂直边缘交叉的水平边缘; (S4000)创建连接到垂直边缘和水平边缘的标签区域代码; (S5000)在输入图像中划分与标签代码区域匹配的标签区域
    • 8. 发明授权
    • 디엔에이 지문영상의 자동분석방법 및 자동분석시스템
    • 自动分析DNA指纹图像及其系统的方法
    • KR101281511B1
    • 2013-07-03
    • KR1020120014646
    • 2012-02-14
    • 전남대학교산학협력단
    • 박상철나인섭한태호이귀상김수형
    • G06F19/10G06T7/00C12Q1/68
    • G06F19/10C12Q1/68G06T7/0012
    • PURPOSE: A method for automatically analyzing a DNA fingerprint image and a system thereof are provided to divide and analyze the DNA fingerprint image into various small images when bending of a lane is generated, thereby accurately detecting the lane. CONSTITUTION: Image data of gel electrophoresis of polymerase chain reaction (PCR) is inputted and stored in a memory unit (120). When an analysis controller (100) reads the image data, an average lane width calculation unit (200) calculates average lane width for the read image data. A continuous area image processing unit (300) reads data which is calculated by the average lane width calculation unit; calculates data of a local maximum point among the image data; and removes a local maximum point which is wrongly calculated and detected. Lanes are detected by connecting local maximum points which the local maximum point, which is wrongly detected, is removed. [Reference numerals] (100) Analysis controller; (120) Memory unit; (200) Average lane width calculation unit; (210) Vertical projection profile processing unit; (220) K-means processing unit; (230) Lane width calculation unit; (300) Continuous area image processing unit; (310) Horizontal projection profile processing unit; (320) Image division processing unit; (330) Divided image vertical projection processing unit; (340) Local maximum point search unit; (350) Error local removal processing unit; (360) Lane configuration processing unit; (370) False lane removal processing unit; (400) Accuracy-reproductivity calculation unit
    • 目的:提供一种自动分析DNA指纹图像的方法及其系统,用于在生成车道弯曲时将DNA指纹图像分割并分析成各种小图像,从而准确地检测车道。 构成:聚合酶链反应(PCR)的凝胶电泳图像数据被输入并存储在存储单元(120)中。 当分析控制器(100)读取图像数据时,平均车道宽度计算单元(200)计算读取的图像数据的平均车道宽度。 连续区域图像处理单元(300)读取由平均车道宽度计算单元计算的数据; 计算图像数据中的局部最大点的数据; 并删除错误计算和检测到的局部最大点。 通过连接本地最大点(错误检测到的局部最大点)被去除来检测车道。 (参考号)(100)分析控制器; (120)存储单元; (200)平均车道宽度计算单位; (210)垂直投影轮廓处理单元; (220)K-means处理单元; (230)车道宽度计算单位; (300)连续区域图像处理单元; (310)水平投影轮廓处理单元; (320)图像分割处理单元; (330)分割图像垂直投影处理单元; (340)本地最大点搜索单位; (350)错误本地删除处理单元; (360)车道配置处理单元; (370)虚假车道拆除处理单元; (400)精度 - 再现性计算单位
    • 9. 发明授权
    • 폐 시티에서 좌우 폐의 영역을 분리하는 방법, 그 방법을 수행하기 위한 프로그램이 저장된 컴퓨터로 읽을 수 있는 매체 및 그 프로그램이 저장된 서버 시스템
    • 分离方法使用顺序CT图像的3D信息,计算机可读存储介质实施方法和存储程序的系统的分离方法
    • KR101092470B1
    • 2011-12-13
    • KR1020100130269
    • 2010-12-17
    • 전남대학교산학협력단
    • 박상철나인섭김수형이귀상
    • A61B6/03G06T9/20
    • PURPOSE: A method for separating a CT picture of a lung into right/left lung areas, a computer readable medium with a program for performing the method, and a server system with the program are provided to automatically and quickly separate one area connected to a left lung area and a right lung area in a CT picture about a lung into right/left lung areas, thereby obtaining high reliability during separation. CONSTITUTION: Tomography images of a lung CT are successively inspected. A current tomography image(100CI) is detected. An area(100ab) where right/left lungs are connected to each other exists in the current tomography image. A left lung boundary line and a right lung boundary line are detected. A pair of pixels are extracted among pixels in the left lung boundary line and pixels in the right lung boundary line wherein the pair of pixels are closest. The location of the central point between the pair of pixels is calculated.
    • 目的:一种将肺部CT图像分离为右肺/左肺区域的方法,具有用于执行该方法的程序的计算机可读介质以及具有该程序的服务器系统,用于自动且快速地将连接到 左肺区域和右肺区域的CT图像中的肺部进入右/左肺区域,从而在分离期间获得高可靠性。 构成:依次检查肺CT的断层摄影图像。 检测当前断层图像(100CI)。 在当前断层图像中存在右肺/左肺彼此连接的区域(100ab)。 检测左肺边界线和右肺边界线。 在左肺边界线的像素和右肺边界线中的像素最靠近的像素之间提取一对像素。 计算一对像素之间的中心点的位置。
    • 10. 发明公开
    • 가우시안 혼합 모델 및 알지비 클러스터링을 이용한 오브젝트 분할방법
    • 通过组合高斯混合模型和RGB聚类的对象分类方法
    • KR1020130078130A
    • 2013-07-10
    • KR1020110146905
    • 2011-12-30
    • 전남대학교산학협력단
    • 오강한박상철나인섭김수형
    • G06T7/00
    • G06K9/00577G06T7/10
    • PURPOSE: An object dividing method using a gaussian mixture model and an RGB clustering is provided to automatically divide an object domain of an object material on an input image without a direct handling by a user. CONSTITUTION: A first sub image generator leads a computer equipment to calculate normal distributions of pixels of each input image, and to produce a first sub image generator (S1200). A second sub image generator leads the computer equipment to calculate color mean values of each candidate area, to calculate Euclidean distance between the each pixel and the each color mean value, and to produce a second sub image (S1300). An object divider leads the computer equipment to produce a result image comprising the object division area comprising the pixels which are positioned on an overlapped spot among each pixel of the first and second object candidate area (S1400). [Reference numerals] (S1100) Output image format is converted to RGB color format; (S1200) First sub image generator leads a computer equipment to calculate normal distributions of pixels of each input image, and to produce a first sub image generator; (S1300) Second sub image generator leads the computer equipment to calculate color mean values of each candidate area, to calculate Euclidean distance between the each pixel and the each color mean value, and to produce a second sub image; (S1400) Object divider leads the computer equipment to produce a result image comprising the object division area comprising the pixels which are positioned on an overlapped spot among each pixel of the first and second object candidate area; (S1500) Result images are converted into a divided binary area, a largest binary area is set as an object area, other areas are set as noises and removed; (S1600) Pixels matched with each pixel coordiate of an object area are created as an object block
    • 目的:提供使用高斯混合模型和RGB聚类的对象分割方法,用于在用户直接处理的情况下,自动划分输入图像上的对象材料的对象域。 构成:第一子图像生成器引导计算机设备计算每个输入图像的像素的正态分布,并产生第一子图像生成器(S1200)。 第二子图像生成器引导计算机设备计算每个候选区域的颜色平均值,以计算每个像素与每个颜色平均值之间的欧几里德距离,并产生第二子图像(S1300)。 对象分割器引导计算机设备产生包括包括位于第一和第二对象候选区域的每个像素之间的重叠点上的像素的对象分割区域的结果图像(S1400)。 (附图标记)(S1100)输出图像格式被转换为RGB颜色格式; (S1200)第一子图像生成器引导计算机设备来计算每个输入图像的像素的正态分布,并产生第一子图像生成器; (S1300)第二子图像生成器引导计算机设备计算每个候选区域的颜色平均值,计算每个像素之间的欧几里德距离和每个颜色平均值,并产生第二子图像; (S1400)对象分割器引导计算机设备产生包括对象分割区域的结果图像,该对象分割区域包括位于第一和第二对象候选区域的每个像素之间的重叠点上的像素; (S1500)将结果图像转换为分割二进制区域,将最大二进制区域设置为对象区域,其他区域设置为噪声并移除; (S1600)创建与对象区域的每个像素协调匹配的像素作为对象块