如何根據(jù)視野范圍選擇遠(yuǎn)心鏡頭

視野指使用照相機(jī)以后看到的物體側(cè)的范圍，首先我們先了解一下視野的計(jì)算方法。

如何根據(jù)視野范圍選擇遠(yuǎn)心鏡頭

視野指使用照相機(jī)以后看到的物體側(cè)的范圍，首先我們先了解一下視野的計(jì)算方法。視野的大小通常與照相機(jī)的有效區(qū)域及倍率有關(guān)，一般知其二便可選擇，不同的相機(jī)靶面大小不一，其所呈視野也不盡相同，通常來(lái)說(shuō)視野可以從以下公式算得：有了視野之后我們即可找到滿足要求視野的鏡頭，通常來(lái)說(shuō)，對(duì)于雙遠(yuǎn)心鏡頭和物方遠(yuǎn)心鏡頭其最大視野不變，我們只需再確定使用相機(jī)之后便可選擇合適的倍率。 例如光虎視覺的OTL11.5-20-65C，其倍率，相機(jī)靶面和工作距都已明確標(biāo)明，11.5表示2/3”靶面的相機(jī)，20指其倍率為2，65為其工作距離（單位mm），那么如何根據(jù)這些參數(shù)看是否滿足我們的需求呢？ 例如，我們需要檢測(cè)一個(gè)尺寸為4mm的螺母外徑，但是由于位置關(guān)系可能需要5.5mm左右的視野，相機(jī)就用2/3”靶面的那么其2倍的遠(yuǎn)心鏡頭是否滿足要求只需把視場(chǎng)和傳感器尺寸帶入公式（1）即可，算出其倍率為是2.09。而2倍的視野能達(dá)到5.75，所以滿足要求。當(dāng)然，客戶的需求千變?nèi)f化，為了更好的服務(wù)顧客，我們還有0.5倍、0.8倍、1倍的等等，為了滿足差異化需求我們還有高分辨率和大景深兩種類型！ 當(dāng)然還有鏡頭像面與靶面不一樣的時(shí)候，其視野該如何計(jì)算呢？ 第一種，鏡頭的像面大于靶面 比如，我們選擇TTL18.5-45-65C鏡頭，其像面尺寸為18.5，倍率為0.411但是相機(jī)靶面為11.5，由于相機(jī)為呈像設(shè)備其視野=相機(jī)靶面尺寸/倍率也就是11.5/0.411= 27.98mm，而該鏡頭視野能達(dá)到45mm。所以會(huì)出現(xiàn)如圖1所示情況，其鏡頭的部分視野會(huì)被浪費(fèi)。圖1.像面尺寸大于靶面尺寸第二種，像面尺寸小于相機(jī)靶面尺寸 圖2.像面尺寸小于靶面尺寸比如我們用TTL11.5-45-65C，其倍率為0.256，但是我們用1’’的相機(jī)時(shí)，帶入公式（1），算得其最大視野為18.5/0.256=72.27m。 然而，如圖2所示，sensor上的四周會(huì)有光線盲點(diǎn)，其所成現(xiàn)出來(lái)的圖像四角為黑色，俗稱暗角，黑影。 第三種，優(yōu)選鏡頭與相機(jī)靶面契合 所以我們?cè)谶x擇鏡頭時(shí)要注意與相機(jī)的配合，只有合適的相機(jī)與鏡頭配合才會(huì)既不浪費(fèi)鏡頭性能也不影響成像質(zhì)量，如圖3，一般鏡頭靶面尺寸稍大于sensor傳感器對(duì)角線尺寸即可，這樣既不浪費(fèi)鏡頭性能，也能有更好的成像質(zhì)量。 圖3. 像面尺寸等于靶面尺寸 當(dāng)然這只是鏡頭選擇要素的一部分，具體還要考慮分辨率和工作距離等參數(shù)，詳情可參考往期內(nèi)容“遠(yuǎn)心鏡頭如進(jìn)何進(jìn)行參數(shù)選型”。 光虎光學(xué)專業(yè)生產(chǎn)由德國(guó)設(shè)計(jì)的工業(yè)鏡頭。以高精度雙遠(yuǎn)心鏡頭為核心，涵蓋高性能FA定焦鏡頭、變倍鏡頭等產(chǎn)品?？蓪?shí)現(xiàn)為客戶定制化研發(fā)生產(chǎn)。光虎光學(xué)還代理歐美日機(jī)器視覺全系列產(chǎn)品。如面陣與線掃工業(yè)相機(jī)、智能相機(jī)、3D相機(jī)、紅外與紫外相機(jī)、光源、圖像采集卡、機(jī)器視覺軟件及其他周邊產(chǎn)品。http://www.gggddd.com.cn/

【視覺知識(shí)】紫外線在機(jī)器視覺中的使用

紫外線在機(jī)器視覺中的使用 什么是UV紫外線？ UV是波長(zhǎng)范圍為10-400nm的電磁輻射，分為三個(gè)不同的波段。在300-400nm之間，光譜的波段稱為近UV波段，分為UV-A（315-400nm）和UV-B（280-315）子波段。在300nm以下，UV-C波段覆蓋100-280nm的波長(zhǎng)。在機(jī)器視覺應(yīng)用中，最常用的是UV-A波段中的波長(zhǎng)，最常見的是365nm和395nm波長(zhǎng)。 紫外線可用于機(jī)器視覺應(yīng)用中，以檢測(cè)使用可見光無(wú)法檢測(cè)到的特征。由于紫外線被許多材料吸收，因此可以捕獲產(chǎn)品表面的圖像，并且由于它的波長(zhǎng)比可見光短，因此會(huì)被產(chǎn)品上的表面特征所散射。 光虎視覺認(rèn)為紫外線可以以兩種不同的方式應(yīng)用于機(jī)器視覺系統(tǒng)。在UV照明反射成像應(yīng)用中，將UV光施加到對(duì)象并使用對(duì)UV敏感的單色或彩色相機(jī)捕獲。在紫外熒光成像中，對(duì)象的表面再次用紫外光照射。在添加了熒光增白劑的產(chǎn)品中，例如油漆，塑料，印刷油墨和染料，這些熒光材料將吸收紫外線輻射，然后再輻射更長(zhǎng)的擴(kuò)散波長(zhǎng)。吸收光譜和發(fā)射光譜的最大譜帶位置之間的波長(zhǎng)差稱為斯托克斯位移（圖1）。<img src="data:image/png;base64,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

視覺引導(dǎo)抓取應(yīng)用中的手眼系統(tǒng)介紹

什么是手眼系統(tǒng) 在機(jī)器人技術(shù)中，手眼系統(tǒng)指的是一個(gè)視覺系統(tǒng)直接連接到機(jī)械臂上，通常位于最后一個(gè)關(guān)節(jié)的后面。換句話說(shuō)，視覺系統(tǒng)與機(jī)械臂一起移動(dòng)。這種方法在機(jī)器人技術(shù)中是相當(dāng)新的，并且為較為傳統(tǒng)的視覺系統(tǒng)的固定安裝提供了替代方案，通常高于機(jī)器人的工作距離。雖然手眼方法可能使許多應(yīng)用受益，但它的潛力在很大程度上受到標(biāo)準(zhǔn)視覺系統(tǒng)的限制。 手眼系統(tǒng)的優(yōu)點(diǎn) 手眼方法在特定的應(yīng)用中非常有用，因?yàn)樗裙潭ㄒ曈X系統(tǒng)方法有更多的優(yōu)勢(shì)。首先，它可以覆蓋更大的掃描量，因?yàn)樗梢詫ｉT針對(duì)感興趣的領(lǐng)域，靈活性更好。因此，視覺系統(tǒng)只受機(jī)器人的范圍限制而不受其自身掃描體積的限制。 由于掃描距離是決定掃描精度的主要參數(shù)之一，相對(duì)于掃描距離較大的固定視覺系統(tǒng)，掃描距離較短的手眼視覺系統(tǒng)可以提供更高層次的細(xì)節(jié)。如果客戶有一個(gè)裝滿小零件的大箱子，那么通過(guò)使用安裝在機(jī)械臂上的掃描范圍較短的小型掃描儀，就可以實(shí)現(xiàn)最高水平的細(xì)節(jié)。因此，機(jī)器人可以通過(guò)掃描儀從最佳距離拍攝箱子內(nèi)的物體，并從不同的角度和角度掃描各個(gè)零件。但是，當(dāng)一個(gè)固定的視覺系統(tǒng)能夠提供符合預(yù)期的細(xì)節(jié)水平時(shí)(如Photoneo PhoXi 3D Scanner XL)，建議選擇固定的視覺系統(tǒng)的方法。 從近距離和任何角度掃描料框的能力也有效地消除了與陰影相關(guān)的挑戰(zhàn)。用固定的視覺系統(tǒng)安裝在料框上方很可能會(huì)導(dǎo)致料框的某些部分投射陰影，從而妨礙對(duì)某些部件進(jìn)行相應(yīng)的點(diǎn)云采集。在這種情況下，需要找到掃描儀相對(duì)于料框的最佳位置，有時(shí)甚至需要手動(dòng)重新放置零件。手眼系統(tǒng)就可以輕松克服這一挑戰(zhàn)。 光虎視覺認(rèn)為手眼系統(tǒng)是一種越來(lái)越受歡迎的方法，在越來(lái)越多的機(jī)器人應(yīng)用中站穩(wěn)了腳跟。隨著協(xié)作機(jī)器人的興起，手眼系統(tǒng)的優(yōu)勢(shì)變得更加明顯。 手眼系統(tǒng)的缺點(diǎn) 首先，相對(duì)于固定的視覺系統(tǒng)而言，手眼系統(tǒng)的安裝更加困難。此外，要找到一種最佳的方式來(lái)處理之前已部署好的線纜也更加困難。 手眼系統(tǒng)的其中一個(gè)缺點(diǎn)是與傳感器發(fā)生碰撞的風(fēng)險(xiǎn)較高，特別是當(dāng)它的尺寸較大時(shí)，很難在機(jī)器人手臂上找到視覺系統(tǒng)的最佳安裝位置。另一個(gè)主要的缺點(diǎn)是機(jī)器人的運(yùn)動(dòng)會(huì)引起振動(dòng)，這是機(jī)器視覺系統(tǒng)無(wú)法處理的。因此，在掃描采集過(guò)程中，機(jī)械臂需要保持靜止，這可能會(huì)延長(zhǎng)周期時(shí)間。因此，對(duì)于時(shí)間緊迫的應(yīng)用場(chǎng)合，手眼方法并不是最恰當(dāng)?shù)慕鉀Q方案。 在光虎視覺看來(lái)，許多情況下，與其選擇安裝步驟比較復(fù)雜的手眼系統(tǒng)，不如選擇帶有高質(zhì)量3D視覺系統(tǒng)的方法，如Photoneo PhoXi 3D Scanner XL。 當(dāng)然，在一些應(yīng)用程序中，手眼法是最好的選擇。在這些情況下，上述手眼系統(tǒng)的缺點(diǎn)可以通過(guò)Photoneo的革命性的“平行結(jié)構(gòu)光”技術(shù)來(lái)克服，這是唯一一種能夠有效抵抗振動(dòng)的3D傳感方法，從而實(shí)現(xiàn)對(duì)移動(dòng)物體的高質(zhì)量3D掃描，而不需要運(yùn)動(dòng)工件。 手眼協(xié)調(diào)運(yùn)動(dòng) 在Photoneo 3D相機(jī)MotionCam-3D中實(shí)現(xiàn)的“平行結(jié)構(gòu)光”技術(shù)，可以實(shí)現(xiàn)手眼協(xié)調(diào)運(yùn)動(dòng)，無(wú)需任何權(quán)衡。MotionCam-3D是唯一能夠在機(jī)械臂運(yùn)動(dòng)期間提供高質(zhì)量掃描的3D視覺系統(tǒng)。該相機(jī)高度抗震動(dòng)，不需要停止機(jī)器人。 由于該技術(shù)能夠捕獲移動(dòng)速度高達(dá)144公里/小時(shí)的物體，所以機(jī)械臂運(yùn)動(dòng)引起的振動(dòng)對(duì)3D點(diǎn)云數(shù)據(jù)的質(zhì)量沒有任何影響。使用該技術(shù)最大的好處是，機(jī)器人不需要停下來(lái)進(jìn)行掃描，與市場(chǎng)上所有其他技術(shù)相比，這大大縮短了循環(huán)時(shí)間。因此，它為新的應(yīng)用打開了大門，例如物體位置的即時(shí)跟蹤。 這一技術(shù)在協(xié)作機(jī)器人的背景下也仍然有意義，因?yàn)槭褂霉潭ㄒ曈X系統(tǒng)能檢測(cè)的缺陷通常非常有限。協(xié)作機(jī)器人本身比工業(yè)機(jī)器人慢，當(dāng)與手眼方法結(jié)合時(shí)，周期時(shí)間甚至更長(zhǎng)。MotionCam-3D克服了這一限制，如果連接到協(xié)作機(jī)器人的手臂上，也能完美地工作。 Motioncam-3D是任何機(jī)器人任務(wù)的終極解決方案——無(wú)論是靜態(tài)場(chǎng)景還是動(dòng)態(tài)場(chǎng)景?；谝曈X系統(tǒng)的手眼方法的局限性現(xiàn)在是一個(gè)過(guò)去的問題。MotionCam-3D為快速掃描提供了很高的分辨率和精度，有效抵抗振動(dòng)，比以往更短的周期。 【來(lái)源：Photoneo 官網(wǎng)】光虎光學(xué)專業(yè)生產(chǎn)由德國(guó)設(shè)計(jì)的工業(yè)鏡頭。以高精度雙遠(yuǎn)心鏡頭為核心，涵蓋高性能FA定焦鏡頭、變倍鏡頭等產(chǎn)品?？蓪?shí)現(xiàn)為客戶定制化研發(fā)生產(chǎn)。光虎光學(xué)還代理歐美日機(jī)器視覺全系列產(chǎn)品。如面陣與線掃工業(yè)相機(jī)、智能相機(jī)、3D相機(jī)、紅外與紫外相機(jī)、光源、圖像采集卡、機(jī)器視覺軟件及其他周邊產(chǎn)品。http://www.gggddd.com.cn/

視覺引導(dǎo)抓取應(yīng)用中的手眼系統(tǒng)介紹

什么是手眼系統(tǒng) 在機(jī)器人技術(shù)中，手眼系統(tǒng)指的是一個(gè)視覺系統(tǒng)直接連接到機(jī)械臂上，通常位于最后一個(gè)關(guān)節(jié)的后面。換句話說(shuō)，視覺系統(tǒng)與機(jī)械臂一起移動(dòng)。這種方法在機(jī)器人技術(shù)中是相當(dāng)新的，并且為較為傳統(tǒng)的視覺系統(tǒng)的固定安裝提供了替代方案，通常高于機(jī)器人的工作距離。雖然手眼方法可能使許多應(yīng)用受益，但它的潛力在很大程度上受到標(biāo)準(zhǔn)視覺系統(tǒng)的限制。 手眼系統(tǒng)的優(yōu)點(diǎn) 手眼方法在特定的應(yīng)用中非常有用，因?yàn)樗裙潭ㄒ曈X系統(tǒng)方法有更多的優(yōu)勢(shì)。首先，它可以覆蓋更大的掃描量，因?yàn)樗梢詫ｉT針對(duì)感興趣的領(lǐng)域，靈活性更好。因此，視覺系統(tǒng)只受機(jī)器人的范圍限制而不受其自身掃描體積的限制。 由于掃描距離是決定掃描精度的主要參數(shù)之一，相對(duì)于掃描距離較大的固定視覺系統(tǒng)，掃描距離較短的手眼視覺系統(tǒng)可以提供更高層次的細(xì)節(jié)。如果客戶有一個(gè)裝滿小零件的大箱子，那么通過(guò)使用安裝在機(jī)械臂上的掃描范圍較短的小型掃描儀，就可以實(shí)現(xiàn)最高水平的細(xì)節(jié)。因此，機(jī)器人可以通過(guò)掃描儀從最佳距離拍攝箱子內(nèi)的物體，并從不同的角度和角度掃描各個(gè)零件。但是，當(dāng)一個(gè)固定的視覺系統(tǒng)能夠提供符合預(yù)期的細(xì)節(jié)水平時(shí)(如Photoneo PhoXi 3D Scanner XL)，建議選擇固定的視覺系統(tǒng)的方法。 從近距離和任何角度掃描料框的能力也有效地消除了與陰影相關(guān)的挑戰(zhàn)。用固定的視覺系統(tǒng)安裝在料框上方很可能會(huì)導(dǎo)致料框的某些部分投射陰影，從而妨礙對(duì)某些部件進(jìn)行相應(yīng)的點(diǎn)云采集。在這種情況下，需要找到掃描儀相對(duì)于料框的最佳位置，有時(shí)甚至需要手動(dòng)重新放置零件。手眼系統(tǒng)就可以輕松克服這一挑戰(zhàn)。 光虎視覺認(rèn)為手眼系統(tǒng)是一種越來(lái)越受歡迎的方法，在越來(lái)越多的機(jī)器人應(yīng)用中站穩(wěn)了腳跟。隨著協(xié)作機(jī)器人的興起，手眼系統(tǒng)的優(yōu)勢(shì)變得更加明顯。 手眼系統(tǒng)的缺點(diǎn) 首先，相對(duì)于固定的視覺系統(tǒng)而言，手眼系統(tǒng)的安裝更加困難。此外，要找到一種最佳的方式來(lái)處理之前已部署好的線纜也更加困難。 手眼系統(tǒng)的其中一個(gè)缺點(diǎn)是與傳感器發(fā)生碰撞的風(fēng)險(xiǎn)較高，特別是當(dāng)它的尺寸較大時(shí)，很難在機(jī)器人手臂上找到視覺系統(tǒng)的最佳安裝位置。另一個(gè)主要的缺點(diǎn)是機(jī)器人的運(yùn)動(dòng)會(huì)引起振動(dòng)，這是機(jī)器視覺系統(tǒng)無(wú)法處理的。因此，在掃描采集過(guò)程中，機(jī)械臂需要保持靜止，這可能會(huì)延長(zhǎng)周期時(shí)間。因此，對(duì)于時(shí)間緊迫的應(yīng)用場(chǎng)合，手眼方法并不是最恰當(dāng)?shù)慕鉀Q方案。 在光虎視覺看來(lái)，許多情況下，與其選擇安裝步驟比較復(fù)雜的手眼系統(tǒng)，不如選擇帶有高質(zhì)量3D視覺系統(tǒng)的方法，如Photoneo PhoXi 3D Scanner XL。 當(dāng)然，在一些應(yīng)用程序中，手眼法是最好的選擇。在這些情況下，上述手眼系統(tǒng)的缺點(diǎn)可以通過(guò)Photoneo的革命性的“平行結(jié)構(gòu)光”技術(shù)來(lái)克服，這是唯一一種能夠有效抵抗振動(dòng)的3D傳感方法，從而實(shí)現(xiàn)對(duì)移動(dòng)物體的高質(zhì)量3D掃描，而不需要運(yùn)動(dòng)工件。 手眼協(xié)調(diào)運(yùn)動(dòng) 在Photoneo 3D相機(jī)MotionCam-3D中實(shí)現(xiàn)的“平行結(jié)構(gòu)光”技術(shù)，可以實(shí)現(xiàn)手眼協(xié)調(diào)運(yùn)動(dòng)，無(wú)需任何權(quán)衡。MotionCam-3D是唯一能夠在機(jī)械臂運(yùn)動(dòng)期間提供高質(zhì)量掃描的3D視覺系統(tǒng)。該相機(jī)高度抗震動(dòng)，不需要停止機(jī)器人。 由于該技術(shù)能夠捕獲移動(dòng)速度高達(dá)144公里/小時(shí)的物體，所以機(jī)械臂運(yùn)動(dòng)引起的振動(dòng)對(duì)3D點(diǎn)云數(shù)據(jù)的質(zhì)量沒有任何影響。使用該技術(shù)最大的好處是，機(jī)器人不需要停下來(lái)進(jìn)行掃描，與市場(chǎng)上所有其他技術(shù)相比，這大大縮短了循環(huán)時(shí)間。因此，它為新的應(yīng)用打開了大門，例如物體位置的即時(shí)跟蹤。 這一技術(shù)在協(xié)作機(jī)器人的背景下也仍然有意義，因?yàn)槭褂霉潭ㄒ曈X系統(tǒng)能檢測(cè)的缺陷通常非常有限。協(xié)作機(jī)器人本身比工業(yè)機(jī)器人慢，當(dāng)與手眼方法結(jié)合時(shí)，周期時(shí)間甚至更長(zhǎng)。MotionCam-3D克服了這一限制，如果連接到協(xié)作機(jī)器人的手臂上，也能完美地工作。 Motioncam-3D是任何機(jī)器人任務(wù)的終極解決方案——無(wú)論是靜態(tài)場(chǎng)景還是動(dòng)態(tài)場(chǎng)景?；谝曈X系統(tǒng)的手眼方法的局限性現(xiàn)在是一個(gè)過(guò)去的問題。MotionCam-3D為快速掃描提供了很高的分辨率和精度，有效抵抗振動(dòng)，比以往更短的周期。 【來(lái)源：Photoneo 官網(wǎng)】光虎光學(xué)專業(yè)生產(chǎn)由德國(guó)設(shè)計(jì)的工業(yè)鏡頭。以高精度雙遠(yuǎn)心鏡頭為核心，涵蓋高性能FA定焦鏡頭、變倍鏡頭等產(chǎn)品?？蓪?shí)現(xiàn)為客戶定制化研發(fā)生產(chǎn)。光虎光學(xué)還代理歐美日機(jī)器視覺全系列產(chǎn)品。如面陣與線掃工業(yè)相機(jī)、智能相機(jī)、3D相機(jī)、紅外與紫外相機(jī)、光源、圖像采集卡、機(jī)器視覺軟件及其他周邊產(chǎn)品。http://www.gggddd.com.cn/

光虎光學(xué)雙遠(yuǎn)心鏡頭和遠(yuǎn)心鏡頭手冊(cè)2023年第2版

光虎光學(xué)技術(shù)手冊(cè) 2021年第4版

為什么使用圖像采集卡？

達(dá)到數(shù)據(jù)傳輸所能達(dá)到的最大吞吐量是工業(yè)和工廠自動(dòng)化的關(guān)鍵標(biāo)準(zhǔn)之一。提高傳感器分辨率和幀率有助于實(shí)現(xiàn)針對(duì)更加高速和高精度物體的捕捉，但與此同時(shí)，會(huì)導(dǎo)致帶寬達(dá)到極限，從而帶來(lái)傳輸上的問題。目前實(shí)現(xiàn)的高帶寬接口，例如25GigE、50GigE接口，就需要將相機(jī)連接到PC上配置的圖像采集卡，從而完成圖像數(shù)據(jù)的傳輸。所以在工業(yè)環(huán)境中使用圖像采集卡，在高傳輸速率和多相機(jī)同步處理方面的應(yīng)用中，是有實(shí)際意義的。 圖像采集卡的意義 了解圖像采集卡的功能和意義是比較重要的，這樣就可以更好地了解其是否可以用于特定的成像系統(tǒng)或應(yīng)用。從本質(zhì)上來(lái)說(shuō)，圖像采集卡能夠?qū)崿F(xiàn)具有同步特性的高分辨率圖像的高速實(shí)時(shí)采集。 圖像采集卡利用PCI總線的功能來(lái)管理從相機(jī)到PC存儲(chǔ)器的圖像數(shù)據(jù)負(fù)載，直接將圖像數(shù)據(jù)從直接存儲(chǔ)器訪問（DMA）移動(dòng)到PC的RAM內(nèi)存，避免了CPU的重載，從而釋放CPU來(lái)執(zhí)行其他任務(wù)。 同時(shí)他它可以接收觸發(fā)信號(hào)和編碼器信號(hào)的輸入，來(lái)達(dá)到和運(yùn)動(dòng)目標(biāo)的無(wú)縫同步。 圖像采集卡的優(yōu)勢(shì) 使用圖像采集卡最大的優(yōu)勢(shì)在于能夠幫助視覺系統(tǒng)實(shí)現(xiàn)最好的傳輸質(zhì)量，即最大化傳輸速度。 可以將所有的采集和I/O同步任務(wù)交給單個(gè)圖像采集卡 可以管理連接的所有外部設(shè)備，包括觸發(fā)和同步 高傳輸速率，CoaXPress采集卡目前可達(dá)50Gbps 可以使用圖像采集卡進(jìn)行圖像預(yù)處理 可以釋放CPU來(lái)進(jìn)行其他任務(wù) <section style="margin:0px

為什么使用圖像采集卡？

光虎視覺代理的圖像采集卡最常用于高速應(yīng)用場(chǎng)景，其對(duì)圖像傳輸速率的要求最大。

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運(yùn)動(dòng)分析介紹及其應(yīng)用

運(yùn)動(dòng)分析基于計(jì)算機(jī)視覺、圖像處理、高速攝影和機(jī)器視覺，研究來(lái)自圖像序列的兩個(gè)或多個(gè)連續(xù)圖像的方法和應(yīng)用，例如由攝像機(jī)或高速相機(jī)捕獲圖像中的明顯運(yùn)動(dòng)的信息。 在最簡(jiǎn)單的情況下，運(yùn)動(dòng)分析處理可以是檢測(cè)運(yùn)動(dòng)，即找到圖像中物體正在移動(dòng)的點(diǎn)。更復(fù)雜的處理類型可以是隨著時(shí)間的推移，來(lái)跟蹤圖像中的特定對(duì)象，將場(chǎng)景中移動(dòng)的同一剛性對(duì)象的點(diǎn)進(jìn)行分組，或者確定圖像中每個(gè)點(diǎn)的運(yùn)動(dòng)幅度和方向。產(chǎn)生的信息通常與序列中特定時(shí)間點(diǎn)的特定圖像相關(guān)，這意味著運(yùn)動(dòng)分析可以產(chǎn)生關(guān)于運(yùn)動(dòng)的時(shí)間相關(guān)信息。 運(yùn)動(dòng)分析的應(yīng)用范圍相當(dāng)廣泛，例如監(jiān)視、醫(yī)學(xué)、電影業(yè)、汽車碰撞安全、彈道槍支研究、生物科學(xué)、火焰?zhèn)鞑サ取?運(yùn)動(dòng)分析的應(yīng)用 最簡(jiǎn)單的運(yùn)動(dòng)分析應(yīng)用之一是檢測(cè)與場(chǎng)景中運(yùn)動(dòng)點(diǎn)相關(guān)的圖像點(diǎn)。這種處理的典型結(jié)果是一個(gè)二值圖像，其中與場(chǎng)景中移動(dòng)點(diǎn)相關(guān)的所有圖像點(diǎn)（像素）都設(shè)置為1，所有其他點(diǎn)都設(shè)置為0，然后對(duì)該二值圖像進(jìn)行進(jìn)一步處理，例如，刪除噪聲、對(duì)相鄰像素進(jìn)行分組并標(biāo)記對(duì)象。分析可以使用多種方法完成：兩個(gè)主要方法為差分法和背景分割法。 1.人體運(yùn)動(dòng)分析 在醫(yī)學(xué)、運(yùn)動(dòng)、視頻監(jiān)控、物理治療、和運(yùn)動(dòng)機(jī)能學(xué)等領(lǐng)域，人體運(yùn)動(dòng)分析已成為一種調(diào)查和診斷工具。人體運(yùn)動(dòng)分析可分為人體活動(dòng)識(shí)別、人體運(yùn)動(dòng)跟蹤、身體及身體部位運(yùn)動(dòng)分析三類。 人類活動(dòng)識(shí)別最常用于視頻監(jiān)控，特別是用于安全目的的自動(dòng)運(yùn)動(dòng)監(jiān)控。該領(lǐng)域的大多數(shù)努力都依賴于狀態(tài)空間方法，其中對(duì)靜態(tài)姿勢(shì)序列進(jìn)行統(tǒng)計(jì)分析并與建模運(yùn)動(dòng)進(jìn)行比較。模板匹配是一種替代方法，可將靜態(tài)形狀模式與預(yù)先存在的原型進(jìn)行比較。 人體運(yùn)動(dòng)跟蹤可以在兩個(gè)或三個(gè)維度上進(jìn)行。根據(jù)分析的復(fù)雜性，人體的表示范圍從基本的簡(jiǎn)筆畫到體積模型。跟蹤依賴于視頻連續(xù)幀之間圖像特征的對(duì)應(yīng)關(guān)系，同時(shí)考慮位置、顏色、形狀和紋理等信息。邊緣檢測(cè)可以通過(guò)比較相鄰像素的顏色或?qū)Ρ榷葋?lái)執(zhí)行，特別是尋找不連續(xù)性或快速變化。三維跟蹤與二維跟蹤基本相同，但增加了空間校準(zhǔn)因素。 身體部位的運(yùn)動(dòng)分析在醫(yī)學(xué)領(lǐng)域至關(guān)重要。在姿勢(shì)和步態(tài)分析中，關(guān)節(jié)角度用于跟蹤身體部位的位置和方向。步態(tài)分析還用于運(yùn)動(dòng)以優(yōu)化運(yùn)動(dòng)表現(xiàn)或識(shí)別可能導(dǎo)致受傷或拉傷的運(yùn)動(dòng)。不需要使用光學(xué)標(biāo)記的跟蹤軟件在這些領(lǐng)域尤其重要，在這些領(lǐng)域中使用標(biāo)記可能會(huì)阻礙自然運(yùn)動(dòng)。 2.制造中的運(yùn)動(dòng)分析 運(yùn)動(dòng)分析也適用于制造過(guò)程。使用高速攝像機(jī)和運(yùn)動(dòng)分析軟件，人們可以監(jiān)控和分析裝配線和生產(chǎn)機(jī)器，以檢測(cè)效率低下或故障。棒球棒和曲棍球棒等運(yùn)動(dòng)器材的制造商也使用高速視頻分析來(lái)研究拋射物的影響。此類研究的實(shí)驗(yàn)設(shè)置通常使用觸發(fā)設(shè)備、外部傳感器（例如加速度計(jì)、應(yīng)變儀）、數(shù)據(jù)采集模塊、高速攝像機(jī)和用于存儲(chǔ)同步視頻和數(shù)據(jù)的計(jì)算機(jī)。運(yùn)動(dòng)分析軟件計(jì)算距離、速度、加速度和變形角等參數(shù)作為時(shí)間的函數(shù)。然后使用這些數(shù)據(jù)來(lái)設(shè)計(jì)設(shè)備以獲得最佳性能。 3.運(yùn)動(dòng)分析的其他應(yīng)用 運(yùn)動(dòng)分析軟件的物體和特征檢測(cè)能力可用于計(jì)數(shù)和跟蹤粒子，如細(xì)菌、病毒、離子聚合物-金屬?gòu)?fù)合材料、微米大小的聚苯乙烯珠、蚜蟲等。 【來(lái)源：光虎光學(xué)內(nèi)部培訓(xùn)資料】 光虎光學(xué)專業(yè)生產(chǎn)由德國(guó)設(shè)計(jì)的工業(yè)鏡頭。以高精度雙遠(yuǎn)心鏡頭為核心，涵蓋高性能FA定焦鏡頭、變倍鏡頭等產(chǎn)品。可實(shí)現(xiàn)為客戶定制化研發(fā)生產(chǎn)。光虎光學(xué)還代理歐美日機(jī)器視覺全系列產(chǎn)品。如面陣與線掃工業(yè)相機(jī)、智能相機(jī)、3D相機(jī)、紅外與紫外相機(jī)、光源、圖像采集卡、機(jī)器視覺軟件及其他周邊產(chǎn)品。http://www.gggddd.com.cn/