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segment image in Chinese

Pronunciation:
How to pronounce "segment image""segment image" in a sentence

Translationmobile phoneMobile

  • 分塊圖像

Examples

  • Recently single - threshold or multi - threshold is often used to segment image and detect object contour on an image by means of genetic algorithm
    本文首先對傳統(tǒng)遺傳算法進(jìn)行了改進(jìn)，提出了適應(yīng)函數(shù)標(biāo)定公式，定義了相似度概念。
  • In final , segmented images were analyzed , and the areas of all different sections of the image were calculated ( presented with pixel number )
    論文最后對分割后的圖象進(jìn)行分析，計(jì)算出了圖象中各部分所占的面積(用象素?cái)?shù)表示) 。
  • We propose a low - dimensional region - based shape index to retrieve images . the initial step in our approach is to segment images into regions on dominant colors
    首先基于主要顏色把圖象分割成區(qū)域，然后把分割后得到的區(qū)域用作形狀檢索的輸入。
  • This algorithm carries out pretreatment of ordinary military graphs , then segments images , extract edges in the margin , and finally conducts feature matching
    該算法實(shí)現(xiàn)了對普通軍事圖像的預(yù)處理,然后進(jìn)行圖像分割、提取邊緣,最后進(jìn)行了特征匹配。
  • Firstly , human skin - color information is used to segment images into skin color region and non - skin color region , then pretreat the skin - color region and come into the phase of image similarity
    首先利用彩色圖像的顏色信息把彩色圖像分割成膚色區(qū)域與非膚色區(qū)域，然后對膚色區(qū)域做預(yù)處理后，進(jìn)入圖像似然度檢測階段。
  • A method based on differential operators is presented for treating sophisticated contours . the algorithm of extracting directional contours from segmented images is also discussed . semi - automatic scheme is proposed
    我們提出了一種新方法，它利用邊界微分算子來盡量在自動(dòng)分類過程中保留圖像特征，還討論了輪廓線的定向提取技術(shù)。
  • Gmrf is a kind of segmentation methods which combine gray characteristic and texture characteristic as its characteristic . gmrf segments image effect . in this method , to combine the mrf and the characteristic which has the guass distribution is the key , and we discussed in the paper
    Gmrf分割作為一種結(jié)合灰度特征與紋理特征的分割方法在圖象分割中得到很好的效果，在gmrf分割方法中，討論了mrf與guass分布結(jié)合條件。
  • The images to be processed is obtained in condition of nonuniform illumination . a threshold surface by interpolating zero - crossing points is used to segment image to avoid influence of nonuniform illumination . then the destination region can be detected using the method of pattern recognition and the method advoid the influence of nonuniform illumination effectively . the contour description is obtained by fitting at least squares principle
    論文在分析當(dāng)前圖象分割的現(xiàn)狀和趨勢的基礎(chǔ)上，采用基于log算子的動(dòng)態(tài)閾值選取對圖象進(jìn)行分割，以克服非均勻光場給圖象分割帶來的影響，然后通過對區(qū)域特征的提取和分類準(zhǔn)則的確定，準(zhǔn)確識別出目標(biāo)區(qū)域。
  • A developed simple m - s model for image segmentation in geometric active contour model is presented based on intra - region similar and inter - region dissimilar properties . the model constructs an energy ( cost ) function , which is made of intra - region variations and weighting squares of subtraction of region mean values . using gradient - descent methods , the energy function is minimized and we get a curve evolution equation that segments image
    基于區(qū)域內(nèi)一致性加權(quán)區(qū)域間差異性構(gòu)造能量函數(shù),利用最陡梯度法使能量函數(shù)最小化,提出了一種改進(jìn)的簡化mumford - shah ( m - s )圖像分割模型,該模型利用區(qū)域內(nèi)方差描述區(qū)域內(nèi)一致性,區(qū)域間平均灰度值之差的平方描述區(qū)域間差異性,實(shí)驗(yàn)結(jié)果表明,通過調(diào)節(jié)加權(quán)系數(shù),該模型對弱邊界圖像分割具有較強(qiáng)的適應(yīng)性。
  • The developed simple m - s model is suitable for weak edge image segmentation by adjusting weighting coefficient . the experiments on tumor ct image segmentation show that geometric active contour model requires more computational load than snake model but it can converiently control the topology construct of segmented image
    在腫瘤ct醫(yī)學(xué)圖像分割實(shí)驗(yàn)中,通過比較參數(shù)活動(dòng)輪廓模型與幾何活動(dòng)輪廓模型可知,參數(shù)活動(dòng)輪廓模型計(jì)算量小于幾何活動(dòng)輪廓模型計(jì)算量,而幾何活動(dòng)輪廓模能適應(yīng)拓?fù)浣Y(jié)構(gòu)的變化。
  • More examples：  1  2
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