binary image 中文意思是什麼
binary image
解釋
比特圖象-
The watermark algovithm can resist the physical transfer of printing and scanning by applying techniques such as fixation normalization mutually which can secure the embedding position, chaotic encipher encryption, multipassage embedding and so on. what ’ s more, the watermark designed in this essay is binary image. it can bear a large amount of information
本文綜合運用了歸一化相關確定嵌入位置、混沌加密、多通道嵌入等技術，使得本文所設計的水印演算法能夠抵抗印刷和掃描的物理轉換過程，同時本文所採用的水印是二值圖像，能夠承載大量的信息。 -
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。 -
The following is the main achievement in this paper : first, to binary image, we proof there are some relation between morphological erosion, dilation and perception model, and generalize the original binary erosive and dilative operation. as a result, we present the concept of degree morphological operation and establish the binary morphological model based perceptional structure
針對二值圖像，證明了數學形態學腐蝕、膨脹運算與感知器模型的關系，並進一步對傳統的二值腐蝕、膨脹運算做了推廣，提出了程度化形態運算的概念，建立了基於感知器結構的二值形態運算模型； 2 -
In this paper, the contrast of original image is enhanced by nonlinear transformation based on the characteristics of grain image ; after comparing several methods of threshold segmentation and analyzing their performance and applicability on grain image, the adaptive threshold segmentation based on gradient image is presented ; the noise of binary image is reduced with morphological filter, the hollow in binary image is filled in and a recognition algorithm is designed to remove agglomerate particle ; on the basis of mathematical morphology two methods are adopted to segment agglomerate grains that are not agglomerated tightly ; the parameters of size and shape, perimeter, area, diameter, complexlity, longest feret diameter, shortest feret diameter etc, are extracted. this technique is applied in measurement of pearl powder ' s particle size
本文根據粒度圖像的特點，採用非線性對比度增強處理改善顆粒顯微圖像的對比度；對多種閾值分割方法進行比較，分析了它們的性能和用於粒度圖像的適用性，在此基礎上提出了一種基於梯度圖像的動態閾值分割方法；對獲取的顆粒二值圖像進行形態濾波和空洞填充，設計了識別演算法去除凝聚體；對重疊不太嚴重的粘結顆粒採用了兩種基於數學形態學的分割演算法；提取了周長、面積、粒徑、復雜度、最長feret徑、最短feret徑等大小和形狀特徵參數，對珍珠粉等粉體粒度進行了測量。 -
- the trace representation and the 2 - adic representation for the dual of the quaternary goethals code are given, and its binary image is proved to be the formal dual of the binary goethals code. - the generalized macwilliams identities are given for the support weight distribution of a quaternary linear code with type 4k and that of its dual code
給出了四元goethals碼的對偶碼的跡表示及2 - adic表示，並證明了它在gray映射下的二元像是二元goethals碼的形式對偶碼；從而可以將對非線性碼二元goethals碼及其形式對偶碼的研究轉化為對四元線性碼的研究； 3 -
Real - time corner detection in binary image
二值圖像中拐點的實時檢測演算法 -
Binary image of the first part of version record
版本記錄的第一部分的二進制圖像。 -
Binary image of the second part of the version record
版本記錄的第二部分的二進制圖像。 -
As a result, we present a simple and high capacity binary image steganography
因此，我們提出了一個簡單並且具有高資料可藏量的黑白影像資訊偽裝術。 -
The main work completed in the paper is listed as following : 1. image function acquisition -, 2. read bmp files by dib format ; 3. drawing gray scale histogram ; 4. choose a optimum threshold and make gray image become binary image -, s. find image ' s contour points by making inner points become empty and apply template matching on the contour points ; 6. transform the object ' s beginning points ( pixel point ) to the ones in the image coordinate and the positions of in the corresponding three dimensions ; 7. compute the position vector and the normal vector of the object
選擇一個最佳闋值，把灰度圖像進行二值化處理； 5用掏空內部點法，找到圖像的輪廓點，然後在輪廓點上進行模板匹配； 6把輸出的目標物開始點（像素點）轉化成圖像坐標系中的點和對應的三維空間的坐標位置； 7計算目標物的位置矢量和法向矢量，根據機器人抓取面的法向矢量，找到機器人要抓取的平面； 8 -
It takes use of pseudo - random technology, dynamic adaptive technology, multi - channel technology, random position embed technology and so no. so the digital watermarking can resist the physical process of printing and scanning. at the same time, the watermark is binary image which includes a great deal of information, such as personal id, secret information, even a piece of map
本文特別針對印刷和掃描給數字圖像帶來的誤差的問題，設計了一種新的水印演算法，綜合運用了偽隨機處理技術、動態自適應技術、不同應用選擇不用頻帶處理技術、隨機位置嵌入技術、多通道嵌入等技術，使得本文所設計的水印演算法能夠抵抗印刷和掃描的物理轉換過程，同時本文所設計的水印是二值圖像，能夠承載大量的信息，例如個人id 、機密信息、商標標識，甚至可以是一幅地圖。 -
In this paper, we firstly design orientation filters based on directional image of fingerprint and employ them to denoise gray - scale image. then, we binarize the gray - scale image with local self - adaptive binarization smoothness algorithm and eliminate the noises from the binary image with fast fourier transform algorithm
本文先基於指紋的方向圖設計出方向濾波器對原圖像進行濾波去噪，然後使用局部平滑閾值自適應二值化演算法，將灰度圖像進行二值化，並採用快速傅氏變換對所得到的二值化圖像進行去噪處理。 -
In the process of production and selection of eye - dots, firstly, the binary image contained human eye region is abstracted by morphological translation, labeled based on connection and the labeled region are assembled into candidates of human eye dots. after the dots are fine tuning based on gray projection calculation, they are chosen ground on gray and edge information
在人眼待選點的產生和篩選過程中，我們首先通過形態學變換提取包含人眼區域的二值圖像；對二值圖像進行基於連通性的標注；標注區域會聚形成候選人眼點；再對候選點進行基於灰度投影積分的小鄰域微調；然後結合灰度信息和邊緣信息進行人眼點的篩選。 -
Visual analysis of human motion has been receiving increasing attention from researchers in the fields of image processing and computer vision during the past few years. it has a lot of applications in virtual reality, smart surveillance system, advanced user interface, motion analysis and video compressing, etc. this paper focuses on the technology of human motion tracking based on video, first, we make a summarization of the domestic and overseas status of the research in this field. on the basis of this, we analyse the technical difficulties of human motion tracking. as most of the existing model - based methods of human motion tracking perform not so good in some situation as they need mannual intervention, and also the precision of tracking is not so satisfying during the research of tracking of walking people because of the self - occlusion of legs, this paper proposes an algorithm of automatic detection and tracking of legs of the walking people based on monocular image sequences, in which we analyse the features of walking people, track the five joints of lower limbs, get various parameters, and then re - construct the walking process. the main research achievement is as follows : 1 ) we propose an algorithm of markerless automatic extraction of leg skeleton. first we divide the video into continuous image sequences, after background subtraction, the satisfying human region could be extracted, then we get a single - connected region by converting the rgb image to binary image and median filtering. afterwards, the contour of lower limbs in the frame with a widest boundingbox is detected, using sobel operator, to find the ankle joint of leg behind according to the features and rules of walking, then, the joint of knee of leg behind, hip, ankle of leg in front, knee of leg in front could be got in turn. so, model of leg skeleton is constructed
首先將視頻分解成許多連續的靜態圖像幀，經過背景去除，把感興趣的人體區域提取出來，通過二值化，中值濾波等預處理方法得到只有人體的一個單連通區域，然後用sobel運算元檢測出boundingbox最寬幀中人體下半身的輪廓，根據運動規律及特徵找到後腿踝關節點，結合從boundingbox最窄幀中所獲取的腿長依次得到後腿膝關節，跨部關節，前腿踝關節，前腿膝關節四點，從而構建出腿部骨架模型。 2 ）實現了人體步行腿部骨架的跟蹤演算法。在完成對腿部骨架模型的自動初始化之後，本文對跨關節、膝關節及踝關節分別採用運動建模、圓周相交定點演算法、運動預測及預測點周圍搜索rgb相似矩形塊三種方法確定每一幀中其實際坐標，從而重構出腿部骨架的運動過程。 -
First, the initial threshold is obtained from the balanced - processing image. second, the binarization of the balanced - processing image is done by increasing the threshold gradually, and the black blocks appearing in the binary image are marked one by one
首先對基於均衡處理后的圖像估計出初始閾值;其次採用閾值遞增法逐次二值化圖像，並對二值圖像中的黑塊逐一標記。 -
By the theoretical analysis and experimental test, the image processing procedure of the system has been designed. firstly, the system needs carry out pre - process : the median filtering and average filtering of acquired image, next carrying out the threshold of filtered image, then performing morphology, such as open, close and so on. next, the boundary of binary image is extracted
通過理論分析與實驗驗證，得到了本系統圖像處理過程:首先對採集的圖像進行預處理，包括均值中值濾波，通過閾值分割進行二值化，然後對二值圖像進行開啟、閉合以及進行邊界提取操作來獲得清晰的圖像邊緣，最後通過邊緣檢測和擬合測量得到沖擊試樣各尺寸值，圖像坐標變換和模式匹配可以完成檢測區域定位。 -
The holes in the binary image after segmenting are removed by " close " algorithm based on morphology
對分割結果採用了形態學閉運算以消除各個體植株間形成的小空洞區域。 -
Firstly the image segments are extracted from binary image based on run - length code matching where each segment represents a section of fingerprint ridge without bifurcation. then the minutiae are determined by defined rules based on the structure of these segments and their link relations
用行程匹配方法提取出代表沒有分支的局部指紋紋線段的圖段，根據圖段的結構形式和圖段之間的連接關系用自定義的規則進行細節點判定。 -
The proposed method accurately and fleetly locates the inner boundary of the iris by means of detecting the diameter of the pupil in the binary image. then, the outer boundary is detected by a deformable circular template
它利用了虹膜瞳孔的生理特徵，在二值化后的虹膜圖像中尋找水平最長弦，從而定位瞳孔的大致位置，在此基礎上經過進一步的細化提取準確的瞳孔中心位置。 -
Extracting 17 morphological features to stored - grain pests binary image, for example area, circle quality, invariable moment and so on. extracting 27 texture features to stored - grain pests " gray image. the morphological features extracted are normalized
針對糧蟲的灰度圖像，提取出基於灰度直方圖、遊程長度和灰度共生矩陣的27個紋理特徵，並對提取的形態學特徵進行歸一化處理。
分享友人