segmentation error 中文意思是什麼

segmentation error 解釋
分段錯誤
  • segmentation : n. 1. 分割；切斷。2. 【生物學】（細胞）分裂；（動物）分節；斷裂。
  • error : n. 1. 錯誤；失錯。2. 謬見，誤想；誤信；誤解。3. 罪過。4. 【數學】誤差；【法律】誤審，違法；（棒球中的）錯打。adj. -less 無錯誤的，正確的。
  1. Both two methods require a good binary image, if there exist concave, the aggregated objects will be segmented and recognized correctly and the error is lower, otherwise, it may give err result. considering the edge information will give robust segmentation, but the information may contain noise when the object is strongly non - uniformity and the speed decreases

    該演算法對圖像的二值化效果要求較高，當物體間的縫隙在二值化后能部分或全部判定為背景，即粘連的物體在二值化后能有明顯的凹陷時，識別率很高，誤差幾乎可以為零。
  2. This paper illustrates detailedly the thin groupware auto - adaptive recognition system ; it also illlustrates the procession of capture image and take indispensable foreclose to wipe off noise in order to get boundary easilyer. the recognition system uses " hough " transform method to make the recognition area orientation, and according to the unstable environment such as lights which leads to the change of the image ' s brightness, thresholds picture using an iterative selection method and then growing process for cell image segmentation based on local color similarity and global shape criteria, adaptively gets the best threshold to divide the washer off the background. the recognition system uses the classifier based on minimal - error - ratio bayes method to make decision after getting image characteristic

    本文詳細介紹了薄形組合件自適應識別系統；闡明了圖像的分通道自動採集過程，以及對採集到的原始圖像所進行的預處理方法。通過採用哈夫變換去除偽邊緣點的方法，有效地解決了識別區域的定位問題。針對裝配零件（主要是墊片）薄、小導致圖像信息少、識別難度大，以及材質不一導致採集到的組合件圖像亮度波動等問題，提出了使用最佳閾值迭代法和使用種子填充的圖像串列分割技術，自適應地找出最佳閡值，使墊片和背景分離，從而提取墊片數目信息。
  3. The study for preprocessing of data points is mainly concentrated on the noise error reduction of cloud point data, data compression, and data segmentation. corresponding algorithm of data preprocessing are

    在數據的預處理上對點雲數據的噪聲點處理、數據壓縮處理和數據的區域分割進行了研究，給出了相應的演算法。
  4. Secondly, image enhancement technique based on linear filtering is adopted. a new image segmentation method by means of automatic multilevel threshold is given, which realizes partial multilevel threshold segmentation based on image region partition of gray - level position projection, removes the influence of uneven illuminance or uneven gray - level distribution on goal recognition, and resolves the problem of error segmentation caused by threshold step between adjacent regions by threshold transition. the method has well robustness

    在圖像處理時，採用基於線性濾波的圖像增強方法，並提出了一種新的自動多閾值圖像分割方法，該方法以基於灰度位置投影的圖像分區實現局部多閾值分割，克服了不均勻照明或不均勻灰度分佈對目標識別的影響，同時，通過閾值過渡很好地解決了相鄰區域閾值「階躍」引起的錯誤分割問題，具有很好的魯棒性。
  5. According to the distribution of chinese single - character after word segmentation in chinese text and the conception of " non - multi - character word error ", we proposed a group of rules to find errors in texts, to construct the automatic error - detection model and to implement its algorithm by combining the scattered single - character bigram models, part - of - speech bigram and trigram models

    根據正確文本分詞后單字詞的出現規律以及「非多字詞錯誤」的概念，提出一組錯誤發現規則，並與針對分詞后單字散串建立的字二元、三元統計模型和詞性二元、三元統計模型相結合，建立了文本自動查錯模型與實現演算法。
  6. However, there are some problems in the original method, such as low availability of the extracted fragments, error position of the match results, and high complexity of the algorithm etc. in this thesis, a novel method to extract fragments is proposed, and it improves the availability of the extracted fragments ; a novel match method called her is also proposed, which is a hybrid one combining the object ’ s edge and region features, and its advancement is showed in the experimental results ; a prototypal top - down image object segmentation system named io - seg is devised and implemented in this thesis, which is based on class - specific fragment and integrates the methods proposed in this thesis

    由於csf - seg方法存在提取的子圖可用性差、匹配位置誤差大、計算復雜性高等問題，通過深入分析和研究，本文提出了一種新的提取子圖的方法，提高了產生的子圖的有效性;在深入研究匹配方法的基礎上，提出了一種新的結合對象邊緣和區域的形狀匹配方法? ? her方法，通過實驗證明了該方法的優越性;最後，結合文中提出的方法設計並實現了一個top - down的圖像對象分割原型系統io - seg 。
  7. Generally speaking, the segmentation method itself could n ' t judge whether there are overlapping bubbles or not in the images ; also could n ' t split them. a concavity detection method of the overlapping bubbles, based on the projection of the object contour is proposed here ; then departing point pair is obtained by matching the concavities ; finally, the splitting curve is obtained by the departing point pair constrained based minimum mean square error ( mmse ) ellipse fitting

    一般說來，圖像分割無法判斷所獲得的氣泡區域是否存在粘連並對其進行分西安理工大學碩士學位論文離，所以本文採用對日標物的輪廓進行投影檢測來尋找氣泡粘連處的凹點，並對凹點進行配對以獲得粘連氣泡的分離點對。
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