image pattern analysis 中文意思是什麼
image pattern analysis
解釋
圖像分析-
Pattern analysis and machine intelligence, 1999, 21 : 1312 - 1328. 3 shen d, wong w, ip h h s. affine - invariant image retrieval by correspondence matching of shape
第三，全局的圖象結構相比局部圖像特徵對噪聲更魯棒，但對圖像畸變卻更敏感。 -
Subareas of image processing include image enhancement, pattern detection and recognition and scene analysis and computer vision
圖像處理的子領域包括圖像增強、模式檢測與識別、場景分析與計算機視覺。 -
The main research fields are pattern recognition, image processing and analysis, computer vision, artificial intelligence, computational intelligence and signal processing
主要研究方向：模式識別、圖象處理與分析、計算機視覺、人工智慧、計算智能和信號處理。 -
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
本文針對上述問題，用計算機圖像處理及模式識別等信息技術對顯微細胞圖像的自動分析和分類的方法進行了研究，並針對醫學圖像分析中的難點（例如，顯微切片圖像背景復雜，分割困難） ，提出了基於歸一化彩色空間和rgb ， hsv彩色模型的兩類分割方法：利用模式識別技術中關于特徵向量空間聚類的方法實施真彩色分割。 -
We designed and made the attraction device to attract agricultural pests, obtained agricultural pests " images with the color camera, processed images based on wavelet analysis. on the basis of these, we emphasized on extracting effective features, put forward recognizing pests " classes with pests " colors and texture features, and succeeded in extracting five efficient features such as color features, wave image edge moments features and so on. then we selected features, inputted into neural network classifier, recognized pattern, presented detection results
本文設計製作了誘捕裝置，誘集農田害蟲，使用攝像頭攝取害蟲圖像，採用小波分析進行圖像處理，在此基礎上重點進行了特徵提取工作，提出了利用害蟲顏色和紋理等特徵進行種類識別的觀點，並成功提取了彩色特徵、小波圖像邊緣矩特徵等五類有效特徵，並經特徵選擇后輸入神經網路分類器進行模式識別，最後給出檢測結果。 -
Secondly, clustering is a promising application area for many fields including data mining, statistical data analysis, pattern recognition, image processing, etc
因其內在的對決策的支持能力，為數據挖掘開辟了新的空間。 -
In this article, pattern recognition is used as theory foundation and image process technology as basic technology. combining with the new theory tools ( wavelet analysis and neural network ), this paper presents effective resolve methods to three parts of image recognition ( image segmentation, image feature extraction and image classificaton ) thought systemic analysis of it
文中以模式識別為基本理論平臺，以圖像處理技術為基本手段，結合新興領域的理論工具（小波分析，神經網路等） ，分別對圖像分割，圖像特徵提取，圖像分類識別三個問題作了系統研究，並提出了有效的解決方法。 -
Clipping the image and judging local threshold are put forward by a lot of experimental analysis, and it works to compensate the influence lead - in by gradient and bended spectral pattern
在大量實驗分析的基礎上提出了剪裁圖像和局部閾值判斷的方法，較好的補償了譜線圖像傾斜彎曲帶來的影響。 -
The important research is about the theory and methods of the cluster analysis in view of statistical theory, the theory and methods of fuzzy cluster analysis, the fkn " s structure and the fkn ' s study algorithm ( fkn, fuzzy kohonen network ) - the organic fusion of the fuzzy c - means algorithm and self - organized feature map neural network. the paper proposes the ifkn ( improved fkn ) on the basis of the hard classification idea and the soft classification idea, then carries on the cluster analysis of the artificial synthetic control chart time series through matlab program and tt ? cluster result matches the cluster result of the famous dataengine " s software of the intellectual data analysis and data mining from german mit company. finally, the paper discusses the applying of the cluster analysis to the control process, which can be widely applied to the pattern recognition of the parameter " s changing trend during the control process and the image partition processing, and utilizes the ifkn to recognize the thermotechnical parameter " s changing trend based on the engineering of clinker sintering rotary kiln automatic control system of guizhou " s aluminium factory, through which good effect is obtained
數據挖掘技術在商業領域中已廣泛使用，然而在工業過程式控制制中的應用卻極少，本文正是在這種背景下，對數據挖掘中的聚類分析方法及其在工業過程式控制制中的應用研究作了償試，重點研究了基於統計理論的聚類分析理論和方法，模糊聚類分析理論和方法及模糊kohonen網路（ fkn ）的結構與學習演算法，即模糊c ? ?均值演算法與自組織特徵映射神經網路（ kohonen網路）的有機融合，並根據硬分類思想及軟分類思想提出了改進的模糊kohonen網路（ ifkn ） ，通過matlab編程對人工合成控制時序圖數據集進行聚類分析，其聚類效果與當今廣泛使用的數掘挖掘軟體平臺，德國mit公司著名的dataengine智能數據分析和數掘挖掘軟體的聚類效果相當，最後，論述了聚類分析在控制中的應用，它可以用於過程式控制制中的參數變化趨勢的模式識別及圖象分割處理等具體應用中，並以貴州鋁廠熟料燒結回轉窯自動控制系統為工程背景，利用ifkn識別其熱工參量變化趨勢，取得了較理想的效果。 -
This scheme covers techniques of texture analysis, synthesis, texture mapping and 3 - d knitting pattern analysis of fabric. we discuss here the techniques related to texture. texture analysis uses frequend - domain, wavelet or mrf to get feature distribution of texture image, classes of texel and the rule of placement
本實現方案涉及到紋理分析、綜合，紋理映射，提花織物三維組織分析等技術，論文主要對與紋理相關的技術作一定的討論，紋理分析運用頻譜、小波分析或馬可夫隨機場建模紋理圖像在空間上的分佈特徵，紋理基元的種類和其分佈。 -
Independent component analysis was first proposed by comon in 1994 to solve the problem of blind source separation, which is now widely used in the area of pattern recognition, image processing and medical science
獨立分量分析ica最初是由comon等人於1994年提出的，它解決了盲源分離等問題，應用於模式識別、圖像、醫學等領域。 -
This paper is concerned with the popular texture analysis technique in the traditional image recognition, the novel pattern recognition approach, namely synergetic neural network pattern recognition, and their applications. furthermore, it proposes and implements an offline handwriting identification multi - classifier. it is organized as follows
本論文研究了傳統圖像識別方法中常用的紋理分析法及一種新的模式識別方法? ?協同神經網路模式識別法及其應用，並在此基礎上構造了一個離線手寫體筆跡鑒別多分類器模型。 -
Object - oriented image analysis creates meaningful objects and builds a hierarchy levels close to surface character using multi - scale segmentation. different geography processes could be represented in corresponding image object levels. object - oriented image analysis has realized multi - scale analysis of spatial pattern and process
面向對象影像分析採用影像分割技術生成多尺度影像對象，構建與地表實體相似的層次等級結構，不同等級的地學過程可在相應尺度的影像對象層中得到反映，實現了空間格局與過程的多尺度影像分析。 -
According to the requirement of chromatic dislocation inspection application in printing industry, this paper combines ccd measurement technology, image analysis technology with pattern recognition theory
本論文根據印刷工業中提出的套色錯位監測這個實際課題要求，把當今的ccd測量技術，圖像分析技術與模式識別理論結合在一起，將圖像分析引入計量測試。 -
With the development of pattern recognition, and image processing methods begin widely used in medicine. automatic chromosome analysis becomes possible. the automatic karotyping will increase then efficiency of availability, and relax then medical persons, it can be performed by the operators who have no professional technology and experiences. at then same time then remote chromosome analysis becomes possible
模式識別技術的發展，以及圖像處理技術在醫學中的廣泛應用，使得自動化染色體分析成為可能，利用計算機進行染色體自動分析會大大提高工作效率，也減輕了醫護人員的負擔，並且它不依賴于工作人員的狀況，工作人員也不需要專家級的技術和經驗，同時也為染色體分析遠程醫療提供了可能。 -
It is widely acknowledged that it is a basic subject in remote sensing applications. image information with different scale displays distinct spatial structure, so image analysis with single scale could not meet the heterogeneity and dynamic of pattern and process
遙感影像是對具有尺度依賴性的空間格局與過程的反映，不同尺度的遙感信息反映著地表特性不同層次的空間結構差異，單尺度的影像分析已不能滿足反映空間格局與過程異質性與動態性的需要。 -
By three steps mentioned above, the automated classification of facial expression is realized. in this paper, an automatically facial expression analysis system is constructed based on the image processing and pattern recognition
本論文的研究主要利用了圖像處理方法和模式識別知識對人臉表情進行自動分類，實現了一個人臉表情自動分析系統。 -
Wavelet analysis is the most perfect combination of the function al analysis. fourier analysis and numerical analysis wavelet analysis has been widely used in signal processing, image manipulation, voice analysis, pattern recognition, quanta physics, biomedicine engineering, computer vision, fault diagnosis, some nonlinear fields and so on. the dissertation is outlined below
小波分析是一個新的數學分支，它是泛函分析、傅里葉分析、數值分析的最完美結晶；在應用領域，特別是在信號處理、圖象處理、語音分析、模式識別、量子物理、生物醫學工程、計算機視覺、故障診斷及眾多非線性科學領域都有廣泛的應用。 -
As a new embranchment of mathematics, wavelet analysis is the most perfect combination of the functional analysis, fourier analysis and numerical analysis. wavelet analysis has been widely used in signal processing, image manipulation, voice analysis, pattern recognition, quanta physics, biomedicine engineering, computer vision, fault diagnosis, some nonlinear fields and so on. in this dissertation, the fault diagnosis techniques based on wavelet analysis were investigated
小波分析是一個新的數學分支，它是泛函分析、傅立葉分析、數值分析的最完美結晶；在應用領域，特別是在信號處理、圖象處理、語音分析、模式識別、量子物理、生物醫學工程、計算機視覺、故障診斷及眾多非線性科學領域都有廣泛的應用。
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