optimal segmentation 中文意思是什麼
optimal segmentation
解釋
最優分割法- optimal : adj. 最適宜的；最理想的；最好的 （opp. pessimal）。
- segmentation : n. 1. 分割；切斷。2. 【生物學】（細胞）分裂；（動物）分節；斷裂。
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Optimal linear combination for segmentation of leukocyte images
白細胞圖像的最優線性組合分割方法 -
Genetic algorithm, as a computational model simulating the biological evolution process of the genetic selection theory of dar - win, is a whole new global optimization algorithm and is widely used in many fields with its remarkable characteristic of simplicity, commonability, stability, suitability for parallel processing, high - efficiency, and practibility. on the other hand, there are many op - timization problems in the field of digital image processing, such as image compression, pattern - recognition, image rectification, image segmentation, 3d image recovery, image inquiry, and or so. in fact all these problems can be generalized as the problem of searching for a global optimal solution in a large solution space, which is the classic application field of genetic algorithm
遺傳演算法是模擬達爾文的遺傳選擇和自然淘汰的生物進化過程的計算模型，是一種新的全局優化搜索演算法，具有簡單通用、穩定性強、適于并行處理以及高效、實用等顯著特點，在很多領域得到了廣泛應用，另一方面，在圖像處理領域有很多優化問題如圖像壓縮，模式識別，圖像校準，圖像分割，三維重建，圖像檢索等等，實際上都等同於一個大范圍搜索尋優問題，而最優化問題是遺傳演算法經典應用領域，因此遺傳演算法完全勝任在圖像處理中優化方面的計算。 -
Dynamic segmentation technology is used to resolve the mutual operation problem between fixed spatial element and abundant attribute data, thus favorable foundation is formed to develop hngis with full functions. ( 2 ) this paper systematically analyzes the characteristics of traffic transit in highway network, explains the relative problems about inquire for the optimal route in highway network. it analyzes the factors affecting users making choice, determines the choice object of transit route : integrated evaluation system of link impedance is formed
系統分析了公路網空間實體集以及它們之間的關系，提出了公路網gis數據的具體組織方法，其中涉及到信息圖層空間劃分、公路網gis數據編碼、數據庫的設計等內容：提出採用動態分段（ dynamicsegmentation ）技術來解決固定空間要素與海量屬性數據的關聯和互操作問題，為研究開發完全功能的公路網gis打下了良好的基礎。 -
A novel method of content - based image segmentation using deformable template matching is proposed. a two - dimensional ( 2 - d ) deformable template based on orthogonal curves is built by pre - computing extensions of the deformable template along orthogonal curves and sampling the curves uniformly. then the definitions of internal and external energy functions are given according to the image segmentation problem, and genetic algorithm is used to obtain globally optimal solutions. the proposed method uses a lower - dimensional search space than conventional methods and reduces the sensitivity of the algorithm to initial placement of the template. experiments on real - world images and in simulations at low signal - to - noise ratio show the robustness and good performance of the method
本文提出一種採用可變形模板匹配技術進行基於內容的圖像分割演算法.通過預先計算出可變形模板沿著變形的正交曲線，並對模板曲線及正交曲線進行離散抽樣，建立一基於正交曲線的二維（ 2 - d ）可變形模板，針對圖像分割問題定義控制可變形模板進行變形的內、外部能量函數，本文採用遺傳演算法搜索能量函數最小的全局最優解.該新演算法比傳統的可變形模板匹配方法降低了搜索空間的維數，減少了演算法對模板初始位置的敏感.對實際圖像及模擬低信噪比圖像處理的結果表明，新演算法具有良好的分割精度及穩定性 -
The paper also analyzes synthetically the effects of some smooth filters prior to image segmentation and indicates that gaussian lowpass filter, a alterable scale filter, is a good choice to establish a balance between the reservation of image details and removal of noise. on the basis of current investigation of actuality and trend of image segmentation at home and abroad, the paper adopts marr operator, called by optimal edge detection to improve greatly efficiency of image segmentation and edge abstract. the sparse edge
論文在分析當前圖象分割的現狀和趨勢的基礎上，採用被稱為最佳邊緣檢測運算元的marr演算法，使圖象分割和邊緣提取的準確性得到了很大的提高；利用人機交互輔助的方法來搜索已經檢出的稀疏邊緣點，並用最小二乘法擬合這些邊緣點，使裝配間隙寬度的測量的精度和準確性得到了極大的保證。 -
In this paper, we present a multi - feature optimal fusion algorithm, inclusive of skin color, to detect one or multiple faces in color image with complex background. it is a hierarchical approach and integrates the skin color segmentation, face template matching and a neural network frontal face detector. with the elimination of false areas, the search area will become smaller and smaller, and the detection will be accomplished eventually
該演算法是一種層次式、由粗到精的檢測方法，按照「分割-搜索」的檢測模式，將膚色分割、平均臉模板匹配與神經網路驗證結合起來，採取逐步排除的方法，一步一步縮小搜索區域，實現彩色圖像中單個或多個正面端正人臉的檢測與定位。 -
We attempt to exploit various machine - learning techniques to learn the heuristic knowledge from users " experiences, so that the image segmentation system can have some human ability in adaptively selecting optimal algorithm and corresponding parameters. learning based image segmentation system can be classified i
希望使用機器學習的技術，通過從用戶對訓練圖像集的分割和評價中學習相應的啟發式知識，以此使系統能夠根據圖像的特徵，為不同的圖像靈活的選擇參數或演算法，從而自動實現令人滿意的分割。 -
Nowadays, the popular image segmentation methods almost take part in the time space of the image, but in this paper, the processed images are transformed form time space to frequency space. thus avoid dealing with isolated pixels in the image, and use correlated phase function as the judgment rule to search for the optimal threshold value from the global solution space
目前，大多數圖像分割方法都是在時域進行的;本文將圖像從時域變換到頻域，避免了對圖像中每一個像素進行單獨處理，使用了相位相關性函數作為評價函數，全局搜索最優解。 -
In order to reduce calculation burden, and at the same time keep image details, we propose optimal initial segmentation method
為了降低融合計算量，同時保持了圖像的細節特徵，提出sar圖像的最優初始分割方法。 -
The result is good for high - resolution images, but is inefficient for middle resolution images. developed another new method for selecting optimal segmentation scale : objects max - area method. the graph that shows the relationship of objects max - area and segmentation scale is ladder like increased
該方法能同時確定影像中多種地物類別的最優分割尺度，證明了不同類別有其相應的最優分割尺度，突破了最優尺度選擇曲線只能適用於一個類別的限制，但該方法只適用於高解析度影像信息提取最優尺度的選擇，對于中低解析度的影像效果不甚理想。 -
Two aspects of optimal scale are exploited in object - oriented image analysis. one is the biggest resolution to extract the smallest class ; the other is the optimal segmentation scale for different classes
提出面向對象影像分析中最優尺度的雙重性：一是提取面積最小類別所需的最大解析度，二是不同類別提取的最優分割尺度。 -
Analysis in one image level that has most pure objects will get high classification accuracy. the optimal segmentation scale means in that image level pure object is most and mix object is lest
影像信息提取在純對象佔多數的尺度層提取能保證有較高的分類精度，因此選擇最優分割尺度也就是選擇影像中純對象最多而混合對象數目最少的分割尺度。 -
Developed a new method for selecting optimal segmentation scale : mean variance method. from the graph many classes " optimal segmentation scales could be got. it proved that for different classes their optimal segmentation scale are different
後者是針對於一種地物類別而言的，影像對象多邊形既不能太破碎，也不能邊界模糊的分割尺度，該尺度下對象大小與特定的地物目標大小接近，且類別內部對象的光譜變異較小。
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