This paper proposed a genetic clustering image segmentation algorithm on entropy 摘要設(shè)計(jì)了一種基于熵的遺傳聚類分割算法。
C - means clustering method for medical color image segmentation and object extraction based on genetic algorithm 均值聚類分割醫(yī)學(xué)彩色圖像
To the noise , singular point , non - face area and the division of face area , this dissertation proposes filter , segmentation by clustering and area combination methods respectively ; to the detection of oriental faces in color images and complex context , the author combines the skin - color model based face rough detection and the ellipse based face location methods to one , then verify the candidate face by abstracting face features . experiment indicates that this algorithm is feasible and highly efficient 針對(duì)類膚色區(qū)域中的噪聲、奇點(diǎn)、非人臉區(qū)域以及人臉區(qū)域被割離的情況,本文提出了濾波、聚類分割、區(qū)域合并等算法;針對(duì)人臉非人臉區(qū)域的的分割,修改并采取了橢圓模板定位的方法;針對(duì)“候選人臉”中出現(xiàn)的“虛警”問題,首先提取人臉面部特征,然后采取人臉驗(yàn)證算法加以驗(yàn)證。
Video object segmentation techniques are discussed , theories and techniques related to video segmentation are introduced and the existing typical algorithms of motion - based and spatiotemporal segmentation are analyzed and compared with the emphasis on analysis of spatiotemporal segmentation algorithms based on 3d region growing 本文以視頻對(duì)象分割技術(shù)為研究課題,首先介紹視頻分割相關(guān)的理論與技術(shù),然后對(duì)現(xiàn)有的基于運(yùn)動(dòng)和基于時(shí)空域相關(guān)兩大類分割算法進(jìn)行對(duì)比研究,并把重點(diǎn)放在基于3d區(qū)域生長的時(shí)空域分割算法的分析上。
In view of the above mentioned problem , the author adopts information technology such as image processing and pattern recognition to research into the method of automatic analysis and classification . in accordance with the difficulty in medical image analysis ( for example , the background of microimage of section is complicated and is difficult to be segmented . ) , the paper puts forward two kinds of segmentation methods based on standardized colorful space and rgb and hsv colorful model 本文針對(duì)上述問題,用計(jì)算機(jī)圖像處理及模式識(shí)別等信息技術(shù)對(duì)顯微細(xì)胞圖像的自動(dòng)分析和分類的方法進(jìn)行了研究,并針對(duì)醫(yī)學(xué)圖像分析中的難點(diǎn)(例如,顯微切片圖像背景復(fù)雜,分割困難) ,提出了基于歸一化彩色空間和rgb , hsv彩色模型的兩類分割方法:利用模式識(shí)別技術(shù)中關(guān)于特征向量空間聚類的方法實(shí)施真彩色分割。