image n. 1.像,肖像,畫像;偶像。 2.影像,圖像。 3.相像的人(或物);翻版。 4.形像,典型。 5.形像化的描繪。 6.【語言學】形像化的比喻,象喻。 7.【心理學】概念,意象;心象。 graven image 雕像。 image frequency 圖像頻(率);鏡頻。 real image 【物理學】實像。 television image 電視像。 virtual image 【物理學】虛像。 God's image 人體。 He is the image of his father. 他活像他父親。 the spitting image of 同…完全一樣的人[物]。 speak in images 用比喻講;說話形像化。 thinking in terms of images 形像思維。 vt. 1.作…的像,使…成像。 2.反映。 3.想像。 4.形像地描畫;用比喻描寫。 5.象征。 adj. -less 缺少形象的。
3 sequential images matching and splicing technology is studied 3研究了長序列動態(tài)圖像匹配與拼接技術。
Background estimation technique based on sequential image time stability 基于序列圖像時間穩(wěn)定性特征的背景估計技術
In this paper , we also present an object detection algorithm for sequential images 本文提出了一個序列圖像中運動目標的檢測算法。
This system is composed of three modules , which are sequential image acquisition , data transport and image processing 系統(tǒng)包括三大模塊:視頻圖,像采集部分、圖像數(shù)據(jù)傳輸部分和圖像后處理部分。
Because the object is far from the camera , and also the outdoor environment has much interference , the background of gathered sequential images is often offset 由于要監(jiān)視的目標區(qū)域離攝像頭比較遠,并且野外環(huán)境的干擾比較大,采集的序列圖像有一定的抖動和位移。
The research interest of moving object detection is image sequence . first , this paper introduces the vision principle of moving object detection and the common methods on sequential images analyzing 運動目標檢測的研究對象是視頻序列圖像,本文首先介紹了運動物體的視覺檢測原理以及序列圖像分析的一般方法。
In chapter five , gained proper matching template taking advantage of edge image and mapped two sequential images basing on image transform and template matching and found moving objects 第五章利用前一章運算得到的邊緣圖像,選取出適當?shù)钠ヅ淠0?,綜合利用中文荷要坐標空間變換和模板匹配法配準圖像,檢測出運動目標。
This paper starts with the running principle and procedure of x - ray sequential image acquisition processing system . the emphasis of this paper is put on key problems of pci device driver based on windows os 本文從x射線醫(yī)學成像的背景、原理和現(xiàn)狀入手,詳細描述了x射線醫(yī)學視頻圖像采集與處理系統(tǒng)工作原理和工作過程。
Therefore , we propose a correspondence approach for feature points in sequential images . in the process of dealing with image sequences , we will revise the match if the offset of image background is big 因此本文研究了序列圖像之間特征點的對應方法,在對圖像序列的處理過程中,若圖像的背景漂移較大,則應進行校正配準。
To recover scene structure from motion , firstly the relation between sequential images must be set up through three steps as feature point extraction , corresponding matching and estimation of fundamental matrices 要恢復場景三維形狀,首先必須建立序列圖像之間的聯(lián)系。其中包括特征點的提取,特征點的匹配以及基本矩陣的估計。