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    • 4. 发明授权
    • 중심 가중치 맵을 이용한 중요도 영역 검출 장치 및 방법, 이를 위한 프로그램을 기록한 기록 매체
    • 使用中心重量掩蔽图和存储介质记录程序检测重要区域的装置和方法
    • KR101517538B1
    • 2015-05-15
    • KR1020130168414
    • 2013-12-31
    • 전남대학교산학협력단
    • 오강한김수형나인섭이칠우
    • G06T7/00G06K9/46
    • G06K9/46G06T5/009G06T5/20G06T7/246G06T7/90
    • 본발명은중심가중치(Centroid Weight Mask, 이하, CWM로기재하도록함) 맵을이용한중요도영역검출장치및 방법, 이를위한프로그램을기록한기록매체에관한것으로서, 특히본 발명에따른중요도영역검출장치는소정영상이입력되는입력부; 상기입력된입력영상으로부터객체로추정되는중요도영역을추출하기위해서컬러(color), Intensity, DoG(Different of gaussian), CWM(Centroid weight map)으로대표되는특징맵들을생성하고, 상기생성한특징맵들을사용하여중요도영역을추출하는제어부를포함하고, 상기 CWM 특징맵은사전정보없이클러스터링을수행하는중심-이동알고리즘(Mean-Shift Algorithm)을기반으로생성하고, 상기중심-이동알고리즘(Mean-Shift Algorithm)을사용하여격자무뉘맵을만들어일부영역픽셀들만계산하여생성된특징맵인것을특징한다.
    • 本发明涉及一种使用重心加权掩码(CWM)图检测优先区域的装置和方法,以及记录其程序的记录介质。 特别地,根据本发明的用于检测优先区域的装置包括:输入单元,用于接收给定的图像输入; 以及用于生成由颜色,强度,高斯差(DoG)和CWM表示的特征图的控制单元,以及通过使用所生成的特征图来提取优先区域。 CWM特征图是一个特征图,其是基于平均移位算法生成的,无需事先信息进行聚类,并且通过使用均值移位创建网格图来生成一些区域的像素 算法。
    • 5. 发明公开
    • 전자기기에서의 동작 인식 시스템 및 방법
    • 用于识别电子设备中的手势的系统和方法
    • KR1020160087423A
    • 2016-07-22
    • KR1020150005983
    • 2015-01-13
    • 전남대학교산학협력단
    • 김영철김수형오강한
    • G06K9/00G06F3/01
    • G06K9/00355G06F3/017
    • 전자기기에서의동작인식시스템및 방법이제공된다. 본발명의일 실시예에따른전자기기에서의동작인식시스템은, 복수개의전위계차센서를이용하여사용자의동작에따른동작신호를추출하는신호추출부; 칼만필터(Kalman Filter)를이용하여상기동작신호에포함된잡음을제거하는잡음제거부; PCA(Principle Component Analysis) 알고리즘을이용하여, 잡음이제거된상기동작신호의차원을축소시키는특징추출부; 및 DTW(Dynamic Time Warping) 알고리즘및 K-NN(K-Nearest Neighbors) 분류기를이용하여, 차원이축소된상기동작신호를인식하는동작인식부를포함한다.
    • 提供了一种用于能够去除手势信号中的小噪声,平滑手势信号以及提高手势信号的识别率的电子装置的手势识别系统及其方法。 根据本发明的实施例,电子设备的手势识别系统包括:信号提取单元,其使用多个位错传感器从用户的手势中提取手势信号; 噪声去除单元,其使用卡尔曼滤波器去除所述手势信号中的噪声; 特征提取单元,其使用主成分分析(PCA)算法来减少从中去除噪声的手势信号的尺寸; 以及手势识别单元,其使用动态时间扭曲(DTW)算法和K-最近邻(KNN)分类器来识别具有减小尺寸的手势信号。
    • 6. 发明授权
    • 영상 내 객체 영역 자동분할 방법
    • 在视频中自动分割对象区域的方法
    • KR101384627B1
    • 2014-04-11
    • KR1020120119574
    • 2012-10-26
    • 전남대학교산학협력단
    • 나인섭김수형오강한
    • G06T7/00
    • G06K9/6261G06K9/40G06K9/4676G06K9/6223G06K9/6247
    • The present invention relates to an automatic segmentation method of an object area in an image and, more specifically, to an automatic segmentation method of an object area in an image which quickly segments an object containing a flower from an image by a probability distribution estimation algorithm. According to an embodiment of the present invention, a time required for segmentation can be minimized as a mobile terminal automatically segments a target object and a background from an input image when the input image of flower or plant is obtained. [Reference numerals] (S1000) Step of converting an image format of input images; (S2000) Step of estimating a predetermined area estimated in which the candidate object is located in the input images as a candidate area; (S3000) Step of extracting each feature information to the candidate object and a background in the candidate area; (S4000) Step of dividing the images in the input image by using the feature information; (S5000) Step of removing the noise of the divided object n the input images
    • 本发明涉及图像中的对象区域的自动分割方法,更具体地,涉及图像中的对象区域的自动分割方法,其通过概率分布估计算法从图像中快速地分割包含花朵的对象 。 根据本发明的实施例,当获取花或植物的输入图像时,移动终端可以最小化分割所需的时间,因为移动终端自动地从输入图像中分割目标对象和背景。 (参考数字)(S1000)转换输入图像的图像格式的步骤; (S2000)将所述候选对象所位于的预定区域估计为所述输入图像作为候选区域的步骤; (S3000)向所述候选对象提取每个特征信息和所述候选区域中的背景的步骤; (S4000)使用所述特征信息来分割输入图像中的图像的步骤; (S5000)去除分割对象在输入图像上的噪声的步骤
    • 9. 发明公开
    • Block Clustering 을 이용한 관심영역기반 자동객체분할방법 및 자동객체분할시스템
    • 基于自动初始估计区域的块聚类对象分类
    • KR1020140047331A
    • 2014-04-22
    • KR1020120113457
    • 2012-10-12
    • 전남대학교산학협력단
    • 나인섭김수형오강한김광복
    • G06T7/00
    • G06K9/6223G06K9/00718G06K9/3233
    • The present invention relates to an automatic object segmentation method for automatically segmenting an object from a background using a block clustering algorithm. The automatic object segmentation method is capable of improving user′s convenience and efficiency by automation to supplement the weakness of providing information on the object by a user in the existing GrabCut implementation. The automatic object segmentation method of the present invention comprises an object interest region estimation step of estimating an interest region of an object for image information including segmentation information of a background and the object. In the object interest region estimation step, cluster dispersion information of an image is analyzed to distinguish the cluster according to the size of a dispersion region, and the image is segmented into the predetermined number of blocks and is determined as an object cluster and a background cluster depending on the object area and the background area within an individual block, and a color mean value of the block.
    • 本发明涉及一种使用块聚类算法从背景中自动分割对象的自动对象分割方法。 自动对象分割方法能够通过自动化来提高用户的便利性和效率,以补充用户在现有的GrabCut实现中提供关于对象的信息的弱点。 本发明的自动对象分割方法包括:对象感兴趣区域估计步骤,用于估计包含背景和对象的分割信息的图像信息的对象的兴趣区域。 在对象感兴趣区域估计步骤中,分析图像的群集色散信息以根据色散区域的大小来区分簇,并且将图像分割成预定数量的块并且被确定为对象簇和背景 取决于单个块内的对象区域和背景区域以及块的颜色平均值。
    • 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