1^35544 九、發明說明：、 【發明所屬之技術領域】 本發明涉及-種虹賴⑽m種可增加顺正確性和資料處 理效率之虹膜辨識系統。 【先前技術】 隨著社會經濟的發展，人們對於安全的問題越來越重視，生物辨識為 近年來非常熱Η的研究題目。目前在生物辨識倾中，湘行為特徵作為 辨識方法中較常見的為透過聲音(v〇ice)、簽名㈤卿㈣進行辨識；而採用 特徵的方法則有臉型(face)、指紋(fm卿邮、視網膜扣㈣、虹膜 ㈣、掌紋_呷，以及掌型㈣)等等。生物辨識即利用身體本身特有 的來做為識別體。由於人類有許多生物特徵錢—無二，加上這些特 徵是跟隨本人，不用擔心被有心人士竊取。 最普遍為人所知的生物_就是缺_，它有著高朗方便性與安 全性’不需要記住複雜的鹤，也不需隨身攜帶餘匙、智能卡之類的東西。 然而，指紋在過去的研究中，還是容易受到外翻纽變研低其辨識率 的缺點’因此日後就有視網膜掃描辨識技術被提H網膜掃描一度成為 籍辨識的主要工具之―，但是視_影像取得必須透過紅外線掃描，而 紅外線或強鑛脆獅人眼會造的傷害，因此，_域辨識技術 便隨之而生。自簡^Le贿dFk)m與位美籍的眼科醫生， 率先利肢膜的特徵作為生細制依據之後，隨著人們對於資訊安全的 要求提升，虹__高職度已漸漸在市場上祕_，重要性已非同 5 1335544 日而語。 虹膜是指瞳關財純的肌肉組織，人的域上魏多微小的凹凸 起伙和條狀組織，具有漏結構。料，人類終其—生虹膜結構幾乎不會 ^任何變化，且其外部包裹絲Μ遭受外相財而改變。 虹膜有著相當獨特且複雜的結構，可以辨識的資訊比人體任何部分都夕， 例如膠原纖維、收縮紋、腺囊、色素、蛇紋微管束、橫紋等等^成夕一1^35544 IX. Description of the Invention: [Technical Field of the Invention] The present invention relates to an iris recognition system capable of increasing cis correctness and data processing efficiency. [Prior Art] With the development of social economy, people pay more and more attention to the issue of safety. Biometric identification is a very hot research topic in recent years. At present, in the biometric identification, the behavioral characteristics of Xiang as the identification method are more commonly identified by voice (v〇ice) and signature (5) Qing (4); while the feature method has face (face) and fingerprint (fm , retina buckle (four), iris (four), palm print _ 呷, and palm type (four)) and so on. Biometrics use the unique features of the body as a recognition object. Since humans have a lot of biometric money – no, and these characteristics are to follow me, don't worry about being stolen by someone who is interested. The most commonly known creature is the lack of _, which has the convenience and security of high lang. It does not need to remember the complicated cranes, and does not need to carry the rest of the keys, smart cards and the like. However, in the past research, fingerprints are still vulnerable to the low recognition rate of the eclipse. Therefore, the retinal scanning identification technology has been promoted as the main tool for identification. Image acquisition must be scanned by infrared rays, and infrared rays or strong mines can cause damage to the human eye. Therefore, _ domain identification technology will follow. Since the ophthalmologist of the United States and the United States, the first to use the characteristics of the limbs as a basis for the production of fines, as people's requirements for information security improve, the rainbow has gradually become on the market. Secret _, the importance is not the same as 5 1335544. The iris refers to the muscle tissue of Shaoguan Caichun. The human body has Wei's tiny bumps and strips, and has a leaky structure. It is expected that the human-like iris structure will hardly change, and its outer wrap will be changed by foreign wealth. The iris has a quite unique and complex structure, and the information that can be identified is more than any part of the human body, such as collagen fibers, shrinkage lines, glandular sacs, pigments, snake-shaped microtubule bundles, horizontal stripes, etc.
共有二百时個㈣之處，她之下，臉部約有Μ個觸處’指咬口有 -十到四十個。據研究指出，兩個人的虹膜相同的或然率為_分之一， 即使是同樣—個人，左右兩眼的虹膜也有著各自的結構。 刀 虹膜識別的過程與指紋識別類似，需聊描的虹膜圖像轉換為數位代 到電腦資料庫。當進行身份識別時，只需比對待檢測者的虹膜圖 射最™驗，^^物似嶋辨識技There are two hundred and four (four) places. Under her, there are about a touch on the face. There are - ten to forty mouthpieces. According to the study, the irises of the two people have the same probability of _, even if it is the same - the individual, the irises of the left and right eyes have their own structure. Knife The process of iris recognition is similar to fingerprint recognition. The iris image to be traced is converted to a digital database. When performing identification, it is only necessary to compare the iris image of the subject to be tested.
【發明内容】 種可增加職正確性和倾處觀率的虹膜辨 本發明之目的係提供一 識系統。 提供-種虹顯識魏，其包含—影侧取装置、— :貝:：、-影像前置處理模组、一特徵抽取處理模組以及一特徵比對 影侧峨梅__個者之嶋像。卿資料料 用來儲存_個虹„彡像_。鄉縣置處賴岭含—曈孔定位單 6 T域輕單元一虹歸彡紅·單元麟―影料料心該瞳 孔德早π絲讀魏睛定傾轉職之瞳孔。該虹膜定位單元 用來以該眼睛影像之瞳孔之圓心像素為圓心，選取一第、早兀 匈131周之—SUMMARY OF THE INVENTION An iris discrimination that increases job correctness and divergence is an object of the present invention. Providing - a kind of rainbow sensation Wei, which includes - shadow side taking device, - : Bay::, - image pre-processing module, a feature extraction processing module, and a feature comparison shadow side 峨梅__ Animated. Qing information is used to store _ a rainbow _ 彡 _ _. Township county is located in Lai Ling containing - pupil positioning single 6 T domain light unit a rainbow 彡 · · 单元 单元 单元 单元 影 影 影 影 π π π π Read the pupil of Wei Jing Ding's job. The iris positioning unit is used to center the center pixel of the pupil of the eye image, and select a first, early and early Hungarian 131 weeks -
第—像素組以及-第二半徑為_之_第二像素組，並依據該第_像素組 之總和以及該第二像素組之總和之差之絕對值，決定該眼睛影像之虹媒區 域。紐W彡像正規化單元絲正聽該虹歷域讀出—錢化虹膜區 域。該影像增強單元用來等化該正規化虹膜區域以產生—等化虹膜區域。 該特徵抽轉峨_概糊⑶賴碰。_比對模組 係用來比_雜虹麵_嚼徵以及複數個域資料。 依據本制之-實關，_孔定位單來二值化麵睛影像，並 自該二值化眼睛影像上選取_第三半徑為圓周之—第三像素組以及一第四 半徑為Μ之-第四像素組，並依據該第三像素組之總和以及該第四像素 組之總和之差之麟值，定健眼睛影像之瞳孔。The first pixel group and the second radius are _ the second pixel group, and the rainbow region of the eye image is determined according to the absolute value of the difference between the sum of the _th pixel group and the sum of the second pixel groups. The New W彡 image normalization unit is listening to the rainbow calendar domain – the Qianhua iris area. The image enhancement unit is configured to equalize the normalized iris region to create an equalized iris region. This feature is transferred to 峨 _ _ paste (3). The _ aligning module is used to compare the _ 虹 面 _ 嚼 以及 以及 以及 以及 以及 以及 以及 以及 以及According to the system-real, _ hole positioning single to binarize the eye image, and select from the binarized eye image _ third radius is the circumference - the third pixel group and a fourth radius is Μ a fourth pixel group, and the pupil of the eye image is fixed according to the sum of the sum of the third pixel group and the sum of the fourth pixel groups.
依據本發明之-實施例，該影賴取裝置包含—第—攝影裝置、一判 斷單元、-第二攝影裝置以及—調整機構。該第_攝影裝置制來拍攝該 使用者之臉㈣像。該觸單元係絲满該制者讀郷像之眼睛部 份是否位於騎娜像之舦位置H攝驟置伽來於該判斷單元 判斷4使用者之臉。陽像之眼睛部份位於該臉料彡像之預設位置時，攝取 該使用者之_靴。朗雜_絲於該_單元鱗職用者之臉 部影像之眼畴份縣位_臉部影像之職位置時，碰該第二攝影裝 置之拍攝位置射鋼整機構包含一步進馬達。該影像娜裝置另包含 7 1335544 —紅外線投射器，用來㈣-波長為·_9GGnm技外線，且該第一 攝影裝置以及鱗二_彡裝置f包含—紅外職鏡(IR Filted來使得只 有波長棚在綱⑻腿之紅外顧過。該觸單元制來二值化該臉部 影像’並自該二值化臉魏睛影像上選取—第五半徑為_之—第五像素 組以及-第六摊周m像缝，並依_第五像纽之總和以 及該第六像素組之總和之差之輯值，判_賴者之料影像之眼睛部 份是否位於該臉部影像之預設位置。 依據本發明之—實細，敍卿像蝴_侧來賴虹膜區域自 極座標轉換為垂直座標。 依據本發明之-實補，姉觀對池係剌纽㈣鄭細 machine) 〇 .依據本發社-實施例，雜徵抽取處理_來則、波轉換的方式 抽取該等化虹膜區域之特徵。 ，配合所 為讓本發.上述和其他目的、贿、和優賴更明顯易懂 附圖式’作詳細說明如下： 實施方式】 請參閱第1圖，第1圖係本發明之虹膜辨識系統1〇之功能方塊圖。虹 膜辨識錢ω包含-影像_置5Q、—影像前置處理模⑽、一特徵 抽取處理模組3G以及，比對模組4G以及—模型資料庫％。影像榻取 8 1335544 裝置50係用來拍攝使用者之眼睛影像5。 像刖置處理模組20用來於接收 -眼睛影像5之後，對眼睛影像5進行前置處 置處理程序，以去除眼白、瞳孔 部份，並將虹膜影像自眼睛影像5取出^ 出特徵抽取處理模組30將虹膜影像 的特徵抽取出來。虹膜辨識系統10可以公 刀為使財簡以及雌使用者兩 個流程。註冊使用者時，首先拍攝使用者人眼影像數張，在影像前置處理 模組W韻抽取處理敏3G_後，麵使用者虹鮮像資料存入 模型資料庫5Q中。辨識使用者時，_樣先經過影像前置處理模組20 以及特徵抽取處賴組3()處理後，再彻齡_組⑽比對模型資料 庫50的内容以產生結果。 請參閱第2 ®，第2 _第i圖之影賴取裝置％之魏方塊圖。影 像擷取裝置50包含-第，織置52、-第二攝驟置％、—判斷單元 56、-調整機構58以及-紅外線投射器％。紅外線投射器55用來射出波 長範圍為700-_nm之紅外線。由於其波長對於人類來說是一種不可見光， 翁較對人眼近距離照射也不會有不適感，加上紅外光對於物體也有良好的 反射作用，可以將虹膜内的紋理清晰的反射出來攝影裝置η以及第 二攝影裝置54之鏡頭外’另包含—紅外職鏡(IRFilter)，只讓7⑻德咖 的紅光線通過，濾除掉其他可見光對影像帶來的影響。為了達到大範圍之 自動追蹤效果，本實施例之影像擷取裝置5〇使用第一攝影裝置52 ,其具有 視野較大之人臉攝影鏡頭來擷取使用者之臉部影像，並利用第一攝影裝置 52所擷取之影像，搭配人臉偵測之機制，將影像擷取裝置5〇做第一階段的 定位。此階段的定位可將人眼影像大略定位於人眼取像的鏡頭，如果畫面 9 1335544 中沒有出現人眼的影像’此第—攝影裝置52將會由中心向外做小範圍的搜 尋。第二階段糊人眼取像的第二攝影裝置54來做準確的定位^第二階段 中，在第二攝影裝置54每一步移動之後，判斷單元％必須判斷晝面中是 否有人目_域於tc讀尋到人_象，即進行拍攝動作。疋 請一併參閱第2圖以及第3^ , m 弟3圖，第3圖係第1圓之影像榻取裝置5 取眼睛影像之錄圖。其包含下列步驟·· 步驟彻：第—攝影裝置52拍攝-使用者之臉部影像。 步驟3㈣_物像之物份是否位於該_像之預設位置。在 本貫知例巾’觸單元％會綱該臉部影像之眼睛部份是否位 位置。若是’執行步驟304，若否，執行步 於該臉部影像之中心 驟310 步驟304 :第二攝影劈罢〇 i 、置54拍攝使用者之眼睛影像。 —:=斷_像是〜心，若是，_ 右否，執行步驟312。 步釋：傳魏目_钟鲍纽單元I 步驟310:調整機構58 58利用-步進巧裝置52之拍攝位置，聰 步㈣：·調整機構58移動調整第二攝广置52之拍攝位置 58係利用〜^ 置之拍攝位置，調整4 達故可微調第二攝影裝置52之拍攝仿 1335544 第一攝影裝置52拍攝臉部影像(步驟_之後，判斷單元52會判斷眼 睛部份是否位版巾*置。嶋目㈣㈣-個灰階值極 低，呈現0_區域，且位於人眼的中心因此_單元&綱用瞳孔的 存在與否’作為觸眼睛部份的位置。首糾斷單元η會與第—攝影裝置 52拍攝臉部影像之所有像素點與-臨界灰階值做比較，當像麵之灰階值 大於該臨界灰階鱗，域像素狀灰難奴為扭，反之，當像素點之 灰階值小⑽轉灰難時，把崎素點之灰階值設定為〇。如此-來，臉 部影像會呈現-彳目像素二值化影像。 月并多閱第4A-4C圖’第4A-4D目係判斷瞳孔半徑範圍之示意圖。 第攝如裝置52所拍攝的臉部影像將過二值化處理後，會呈現如第仏圓 所不之〜像因為瞳孔具有近似圓形的形狀，以下將利用一種稱之為測圓 機制來决疋瞳孔的位置。因為瞳孔在人眼影像巾為像素值最低的區域，所 以瞳孔的邊界就是存在於灰階值變化最大的地方。也就是說，計算内圓(半 徑計1)圓周上各點之像素值總合與外圓(半徑听+_周上各點之像素值 總合之差’若出值最大_形區域__關區域為瞳孔的位置。 舉例來說，觸單元％鍵立—個以像懿〇 心、，兩侧外徑分別為 Γΐ以及Γ〇之同’^圓周遮罩，其中r[<i〇 ’明〇。在&的圓周上取1〇個像素 點A1 Α2 ..·、Α1〇，在r〇的圓周上亦取丨〇個像素點^、Β2、…、則〇， 則内圓周上輕像素值A :⑽以㈤+項·)以及外類上邊點像素 值L和為Ρβ-/>(5ΐ) + Ρ㈣+ +ρ(·) β並計算外圓以及内圓像素總合之差 Ρ-ΙΑ Λ卜對於在大小範圍之内的瞳孔，會得到最高的差值(如第祀圖所 1335544 示)。當判斷單元56判斷具有最高的差值時，即認定臉部影像中含麯 份區域，且判斷單先會判斷像素點〇是否位於臉部影像之中心位置^ 第一攝影裝置52拍攝時，使用者的臉部有所偏差而未拍攝到眼睛，或^ 睛部份並未位於臉部影像中間位置，則調整機構58會調整第—攝影裝^ 的位置，然後再次拍攝使用者之臉部影像，直到判斷單元％判斷臉 中含有眼睛部份區域，且眼睛部份位於臉部影料間位置。 〜 -旦判斷單元56判斷臉部影像中含有眼物純域，且像素點〇位於 騎影紅巾⑽卿二攝難置54會依瓣—絲錢52所決 疋出來的定位點拍攝使用者眼睛影像 目較第-攝影裝置52多，且以像σ _ 攝衫裝置54的像素數 且4像4較佳’所以第二攝影裝置 調拍攝的是解析度較佳的眼睛影像。接下來，判斷裝置％會利用 圓機_第二攝_ 54操取出來的眼_像 中= 像的一，__ 像二 / 作下—步的處理；若否，則調整機構312會調整第二㈣ 、置54的拍攝位置1後再次拍攝使用者之眼睛影像， = 判斷瞳孔位於眼睛影像中間位置。 斷早兀6 第5圖’第5圖係第】圖之影像前置處理模組2 衫像別置處理模组20包含—瞳孔定位單以 膜影像正規化單元26以及—影、疋早兀24、-虹 後，影像前置處理模·㈣會利用瞳孔定位^順㈣獅出來 位以決定眼睛影像之圓心。接著虹膜早7" 22對眼睛影像5的瞳孔定 Ά 24依據眼睛影像之圓心對眼 12 1335544 睛影像5之虹膜邊界蚊位，標示出虹膜所在之環狀區域。之後利用虹膜 敝規化單元26▲膜内徑以及外徑做正規化的動作，將每張虹膜影像 祕至具有彳目軸雜別、°鐘W，麵化單元28會 等化影像的方式來加驗_驗理資訊。According to an embodiment of the invention, the image capture device comprises a -photographing device, a judging unit, a second photographing device and an adjustment mechanism. The first photographing device produces a face image of the user. Whether the eye unit of the touch unit is full of the eye part of the system is located at the position of the rider image, and the camera unit judges the face of the user. When the eye part of the male image is located at the preset position of the face image, the user's shoe is ingested. When the face of the _ unit is used, the position of the image of the county is _ face image, and the position of the second photographic device includes a stepping motor. The image sensor device further includes a 7 1335544-infrared projector for the (four)-wavelength of the _9GGnm technology line, and the first camera device and the scale device _ 彡 device f contain an infrared mirror (IR Filted to make only the wavelength shed) In the infrared of the (8) leg, the touch unit is used to binarize the facial image 'and select from the binarized face image - the fifth radius is _ - the fifth pixel group and - the sixth The square m is stitched, and according to the sum of the sum of the fifth image and the sum of the sixth pixel groups, whether the eye portion of the image of the image is located at the preset position of the face image According to the present invention, the syllabary is converted from a polar coordinate to a vertical coordinate according to the invention. According to the present invention, the actual compensation, the 姊观对池系剌纽(四)郑细machine) 〇. In the case of the embodiment, the feature extraction process is used to extract the characteristics of the equalized iris region. The above-mentioned and other purposes, bribes, and superiors are more clearly understood in the following description of the drawings as follows: Embodiments Please refer to FIG. 1 and FIG. 1 is an iris recognition system 1 of the present invention.功能The function block diagram. The iris recognition money ω includes - image_set 5Q, image preprocessing module (10), a feature extraction processing module 3G, and comparison module 4G and model database %. Image couch 8 1335544 Device 50 is used to capture the user's eye image 5. The image processing module 20 is configured to perform a pre-processing procedure on the eye image 5 after receiving the eye image 5 to remove the white portion and the pupil portion, and extract the iris image from the eye image 5 Module 30 extracts features of the iris image. The iris recognition system 10 can be used as a process for both financial and female users. When registering a user, firstly, a number of images of the user's human eye are taken, and after the image pre-processing module W is extracted and processed to be sensitive 3G_, the surface user's rainbow image data is stored in the model database 5Q. When the user is identified, the image is processed by the image pre-processing module 20 and the feature extraction group 3 (), and then the age group_10 (10) compares the contents of the model database 50 to produce a result. Please refer to the 2nd, 2nd, and 2nd pictures of the Wei block diagram of the device. The image capturing device 50 includes - a first, a weaving 52, a second camera %, a judging unit 56, an adjusting mechanism 58, and an - infrared projector %. The infrared projector 55 is used to emit infrared rays having a wavelength range of 700 - _nm. Because its wavelength is a kind of invisible light for human beings, Weng does not feel uncomfortable when it is close to the human eye. In addition, infrared light has a good reflection effect on the object, and the texture inside the iris can be clearly reflected. The device η and the lens of the second photographic device 54 additionally include an IR filter, which allows only the red light of the 7 (8) de café to pass through, filtering out the influence of other visible light on the image. In order to achieve a wide range of automatic tracking effects, the image capturing device 5 of the present embodiment uses the first imaging device 52, which has a human face lens with a large field of view to capture the facial image of the user, and utilizes the first The image captured by the photographing device 52 is matched with the face detection mechanism to make the image capturing device 5 the first stage of positioning. The positioning at this stage can roughly locate the human eye image to the lens of the human eye. If there is no image of the human eye in the picture 9 1335544, the first camera device 52 will perform a small search from the center outward. In the second stage, in the second stage, after each step of the second photographing device 54, the judging unit % must judge whether there is a person in the face. Tc reads the person _ image, that is, the shooting action.疋 Please refer to Figure 2 and 3^, m brother 3, and figure 3 is the image recording device of the first circle. It includes the following steps: Steps: The first photographing device 52 takes a picture of the face of the user. Step 3 (4) _ The object image is located at the preset position of the image. In the present example, the contact unit % is the position of the eye portion of the facial image. If yes, go to step 304. If no, execute step at the center of the facial image. Step 310: The second camera 劈 〇 i, set 54 to capture the user's eye image. -: = = _ like ~ heart, if yes, _ right no, go to step 312. Step by step: pass Weimu _ Zhong Bao New Unit I Step 310: Adjusting mechanism 58 58 Using the shooting position of the step-by-step device 52, Congbu (4): · Adjusting mechanism 58 moving to adjust the shooting position of the second camera 52 The position of the photographing position is adjusted by 4, so that the photographing of the second photographing device 52 can be fine-tuned. 1335544 The first photographing device 52 takes a facial image (after step_, the judging unit 52 judges whether the eye portion is a t-shirt. * Set. Item (4) (4) - A gray scale value is extremely low, showing a 0_ region, and is located at the center of the human eye. Therefore, the presence or absence of the pupil is used as the position of the eye-touch portion. η will compare with all the pixel points of the face image taken by the first photographing device 52 and the -critical gray scale value. When the gray scale value of the image plane is larger than the critical gray scale scale, the domain pixel gray is difficult to be twisted, and vice versa. When the grayscale value of the pixel is small (10), it is difficult to set the grayscale value of the gray point to 〇. In this way, the facial image will appear as a binarized image of the target pixel. -4CFig. 4A-4D is a schematic diagram for judging the radius of the pupil. After the captured facial image has been binarized, it will appear as the 仏 circle is not ~ like because the pupil has an approximately circular shape, the following will use a so-called rounding mechanism to determine the position of the pupil. Because the pupil is the area with the lowest pixel value in the human eye image towel, the boundary of the pupil is the place where the grayscale value changes the most. That is, the pixel value of each point on the circumference of the inner circle (radius meter 1) is calculated. The difference with the outer circle (radius hearing +_ the sum of the pixel values of the points on the week) is the largest value of the _shaped area __ the closed area is the position of the pupil. For example, the touch unit % key is set to 〇 、 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , 两侧 圆周 圆周 圆周 圆周 ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ Α1〇, on the circumference of r〇 also take a pixel point ^, Β 2, ..., then 〇, then the inner circle of light pixel value A: (10) to (5) + item ·) and the outer class pixel value L And Ρβ-/>(5ΐ) + Ρ(4)+ +ρ(·) β and calculate the difference between the outer circle and the inner circle pixel Ρ-ΙΑ Λ for the size The pupil within the circumference will get the highest difference (as shown in Figure 1335544). When the judgment unit 56 judges that there is the highest difference, it is determined that the face image contains the track area, and the judgment will be Determining whether the pixel point 位于 is located at the center position of the face image. When the first photographing device 52 photographs, the user's face is deviated without photographing the eye, or the eye portion is not located in the middle of the face image, The adjustment mechanism 58 adjusts the position of the first camera, and then captures the user's face image again until the judgment unit % determines that the face contains a part of the eye, and the eye portion is located between the face shadows. Once the judging unit 56 judges that the facial image contains the pure field of the eye object, and the pixel point is located in the riding shadow red towel (10), the second photo is difficult to set 54 and the user's eye image is taken according to the positioning point determined by the flap 52. There are many more than the first imaging device 52, and the number of pixels of the image capturing device 54 is the same as that of the fourth image capturing device 54. Therefore, the second imaging device adjusts the image of the eye with better resolution. Next, the judging device % will use the processing of the eye_image of the circular machine_second camera_54, the image of the image, the __ image of the second/next step; if not, the adjustment mechanism 312 will adjust the 2 (4), set the shooting position of 54 and then take the user's eye image again, = judge the pupil is located in the middle of the eye image.断早兀6 Fig. 5 'Fig. 5' is the image pre-processing module 2 of the image processing module 20 includes the pupil positioning unit to the film image normalization unit 26 and the shadow image 24, after the rainbow, the image pre-processing module (4) will use the pupil positioning ^ Shun (four) lion out position to determine the center of the eye image. Then the iris is 7" 22 to the pupil of the eye image 5 Ά 24 according to the center of the eye image to the eye 12 1335544 eye image 5 of the iris border mosquito position, indicating the annular region where the iris is located. Then, using the iris 敝 gauge unit 26 ▲ membrane inner diameter and outer diameter to do the normalization action, each iris image is secreted to have the eye axis miscellaneous, ° clock W, the surface unit 28 will equalize the image Add _ test information.
由於輸入的眼睛影像5只 位置不一定在眼睛影像5的中 要判斷虹膜的位置’賴先決定瞳⑽位置。 要求包含虹膜以及瞳孔部分的影像，瞳孔的 心。而且虹膜係環繞於瞳孔之圓型物，所以 由於瞳孔灰階值偏低的特性， ^孔定位單元22會先將目晴影像5之所有録點與-臨物做比較， 當像素點之灰階值大於該臨界灰階值時，把該像素點之灰階值設定為况， 反之’當像施之灰階值小浦臨界灰階辦，把該像素點之灰階值設定 為〇如此-來’眼睛影像會呈現一個像素二值化眼睛影像。因為瞳孔半徑Since the position of the input eye image 5 is not necessarily in the eye image 5, the position of the iris is determined to determine the position of the 瞳 (10). The image containing the iris and the pupil part, the heart of the pupil, is required. Moreover, the iris system surrounds the circular shape of the pupil, so due to the low grayscale value of the pupil, the hole positioning unit 22 first compares all the recorded points of the clear image 5 with the object, when the pixel is grayed out. When the order value is greater than the critical gray level value, the gray level value of the pixel point is set to the condition, and conversely, when the gray level value of the gray level is applied, the gray level value of the pixel point is set to be the same. The 'eye image' will present a pixel binarized eye image. Because of the pupil radius
圍約在10 — 30像素大小，且瞳孔在人眼影像中為像素值最低的區域，所 以瞳孔的邊魏是存在於灰階值變化大的地方。也就是說，計算_(半徑 和1)圓周上各點之像素值總合與外圓(半沿〇=Γ+·周上各點讀素值總 合之差，若出現差值最大的半徑Γ=(ΐϊΗ·0) /2的圓形區域即判斷該圓型區域 為瞳孔的位置。舉例來說，瞳孔定位單元22會建立一個以像素點〇為圓心， 兩個内外徑分別為Γι以及化之同心圓周遮罩，其中。在η的圓 周上取10個像素點A1、A2、··.、A10 ’在r〇的圓周上亦叙1〇個像素點 B1、B2'…、B1〇，則内圓周上邊點像素值乃=p(A) + p(A) +…+户(4〇)以及 外圓周上邊點像素值總和為Α =Ρ(51) + Ρ(52) + ··· + Ρ(510)。並計算外圓以及内 13 山）544 圓像素〜。之差ρ = |ρ〇4。對於在大小範圍之内的瞳孔’會得到最高的差 值(如第4C圖所不）。當瞳孔定位單元22觸具有最高的差值時 ，即認定以 像素點0為一估計的瞳孔圓心。The area is about 10-30 pixels, and the pupil is the area with the lowest pixel value in the human eye image. Therefore, the edge of the pupil is present in the place where the grayscale value changes greatly. That is to say, calculate the sum of the pixel values of the points on the circumference of _(radius and 1) and the outer circle (the difference between the half-edge Γ=Γ+·the total reading value of each point on the week, if the radius with the largest difference occurs The circular area of Γ=(ΐϊΗ·0) /2 determines that the circular area is the position of the pupil. For example, the pupil positioning unit 22 establishes a circle centered on the pixel, and the two inner and outer diameters are respectively Γι and a concentric circumferential mask in which 10 pixel points A1, A2, . . . , A10 ' on the circumference of η are also represented on the circumference of r〇 by 1 pixel points B1, B2'..., B1〇 , the pixel value on the inner circumference is =p(A) + p(A) +...+ household (4〇) and the sum of the pixel values on the outer circumference is Α =Ρ(51) + Ρ(52) + ·· · + Ρ (510). And calculate the outer circle as well as the inner 13 hills) 544 round pixels ~. The difference ρ = |ρ〇4. For the pupils within the size range, the highest difference is obtained (as in Figure 4C). When the pupil positioning unit 22 has the highest difference, it is determined that the pixel point 0 is an estimated pupil center.
月參閱第6圖’第6圖係、估計圓心示意圖，陰影部份為可能的圓心位 在利用—值化目叫影像求得瞳孔估計圓^之後，瞳孔定位單元π會將 原先的眼睛影像5顧1Q個像素的區域⑹定為實關心可能位置。接下 來將區域80内所有的像素作為候選的圓心，搭配半徑的〇、r〇>3〇的圓 遮罩在叫〜像5中搜尋。接著計算出内外圓像素差距最大的位置，即為 目里孔之精準位置。由於本實施例先朝二值化的眼睛影像找出瞳孔的估計 ^置斤在的區域8〇，接著利用第二攝影裝置54拍攝的眼睛影像5找尋 實際瞳孔圓讀i，_㈣大大減少搜尋細進⑥提補測的速度。 —彳置確讀’虹财料元24係絲侧虹膜的區域範圍。 因為母個人人眼中瞳孔與虹膜的相對關係、不盡相同，不—定都是同心圓， 所以__細嘴，彳㈣糊雜胁㈣。因此，求 得瞳孔圓心之後，虹跑單元％，並以瞳孔定位單元Μ所烟的瞳孔圓 心〇為圓心，將曈孔圓心〇周 個像素k長颇騎有像素點作為 估汁虹膜圓心，並以内圓半 為個像素，外圓半徑為觸個像素做為圓 遮罩，執行測圓機制以搜尋虹膜區域。 接下來，域雜錢鱗元26會依財齡Ux 一_ 界’將㈣影像自眼睛影像5中切割出來，得—環狀區域影像(由兩^ 及虹膜影像之邊 不同 1335544 心之騎構成)。-缺說，從不同人職取之虹卿像，具林_大小， 即使是同-個人的虹膜，也可能會因為瞳孔的縮放以及拍攝距離的不 同而使内外徑的大小發生變㈣時，瞳孔與虹膜大多時候都並非同心圓， 圓、的偏離程度也因人而異。因此域影像正規化單元％即是用來將不同 的眼睛影像5調整到相同的尺寸和對應的位置，從而消除平移、縮放對於 虹膜辨識_。_彡像正規化單元26將_心定為參考點，對於每 一點作座標變換無至極座標位置，賴成為—固定大小之矩形區塊。 請參閱第7圖，第7圖係虹臈正規化之示意圖。（㈣為知方向，且 介於睛_从虹_之_，即_域。 f孔賴心以及半徑，物為在_上，_叫_邊界的距 離。則虹膜邊界上的-像素點Μ山）滿足： ~xp +i?£(0)xcos(^) Ο) (2) (3) (4) [ys =yP^RL(e)xsm(0) 因此可以得到a =〜-A == ~~及/.) 2 (xs -χβΫ+ (ys ~yB)2= 5| = ^2 從式(1)、（2)、（3)可以推導出尺(0):Refer to Figure 6 in Figure 6 for the outline of the center of the circle. The shaded part is the possible center of the circle. After the value of the target is used to obtain the pupil estimation circle ^, the pupil positioning unit π will image the original eye. The area (6) of 1Q pixels is determined to be a possible position of concern. Next, all the pixels in the area 80 are taken as the center of the circle, and the circle of the radius 〇, r〇 > 3 遮 is searched for in the image ~5. Then calculate the position where the inner and outer circle pixels have the largest gap, which is the precise position of the hole in the mesh. Since the present embodiment first finds the estimated area of the pupil in the binocularized eye image, then the eye image 5 taken by the second photographing device 54 is used to find the actual pupil circle read i, _ (4) greatly reduces the search fine Enter the speed of 6 to make up the test. - 彳 确 ’ ‘ 虹 虹 虹 虹 虹 虹 虹 虹 虹 虹 虹 虹 虹 虹 虹Because the relative relationship between the pupil and the iris in the eyes of the mother is not the same, it is not concentric, so __ fine mouth, 彳 (four) paste the threat (four). Therefore, after obtaining the center of the pupil, the unit is moved to the center of the pupil, and the center of the pupil of the pupil of the pupil is used as the center of the pupil, and the pixel of the pupil is the length of the pixel, and the pixel is taken as the center of the iris. The inner circle is half a pixel, and the outer circle radius is touched by a pixel as a circular mask, and a rounding mechanism is performed to search for the iris area. Next, the domain miscellaneous scales 26 will be cut out from the eye image 5 according to the financial age Ux _ boundary ', and the ring image will be formed by the two sides of the iris image. ). - Lack of saying, from the different people's positions, the image of the rainbow, with the size of the forest, even the same-personal iris, may also change the size of the inner and outer diameters due to the pupil zoom and the shooting distance (four), Most of the pupils and irises are not concentric, and the degree of deviation of the circle varies from person to person. Therefore, the domain image normalization unit % is used to adjust different eye images 5 to the same size and corresponding position, thereby eliminating panning and zooming for iris recognition_. The image normalization unit 26 defines the _ heart as a reference point, and for each point coordinate transformation has no eccentric coordinate position, which becomes a rectangular block of a fixed size. Please refer to Figure 7, which is a schematic diagram of the normalization of rainbow trout. ((4) For the direction of knowledge, and between the eyes _ from the rainbow _, that is, _ domain. f hole reliance and radius, the object is the distance between _, _ _ _ boundary. - the pixel point on the iris boundary Μ Mountain) Satisfaction: ~xp +i?£(0)xcos(^) Ο) (2) (3) (4) [ys =yP^RL(e)xsm(0) Therefore we can get a =~-A = = ~~ and /.) 2 (xs -χβΫ+ (ys ~yB)2= 5| = ^2 From the equations (1), (2), (3), the ruler (0) can be derived:
Rl (0) = \〇PB\ = axcose + ylRs^a2sijie2 正規化時，在每個0方向上， 利用<(0)以及£之比率，將及 映射至展_形中之相對位置W這種映射對於平移和㈣圓:二 Q上每一點 15 變換具有不變性 、通後峨她爾崎A 28卿咖。因為虹膜區 域内紋理_隨小，也就是說，虹_域各像素之灰離會分佈在苹一 段比較小_。_像触單元28切_域_理，其使得所 有灰階值出現的概率_。如第8 _示，第8圖係影像強化單元28執行 等化的方法流程圖，其步驟如下： 步驟800 :列出虹膜區域影像的灰階值r/ 數。 步驟802:統計各灰階值的像素個Km , / = u ]。 步驟謝：計算原始影像直方圖各灰階級的出現頻率⑽其中斤 為虹膜區域影像的全部像素個數。 步驟806 :計算累計分布函數。 步驟齡細gi =_55，）+ ()·5]計算映射後的輸人影像的灰階級 A，i=<U”“，p-7，/>為輸出影像灰階級的個數，其中如為取整 數符號。 ^驟810 .用&和&的投射關係調整原始影像的灰階級，獲得等化後的輸出 虹膜影像。 請繼續參閱第丨圖。特徵抽取處理模組3〇包含一小波轉換單元32，係 將等化後的虹臈影像應用小波轉換法(wavelet)抽取虹膜影像内的主要特 徵。小波轉換—般被應用在一維的訊號處理或是二維的影像壓縮上，作法 1335544 都疋利用小波轉換後將等化後的虹膜影像分解成高頻與低頻兩部分。高頻 孔號包含邊緣資訊或是雜訊，低頻訊號則近似於等化後的虹膜影像，所以 特徵抽取處理模组3〇會捨棄掉高頻訊號而留下低頻訊號以加速傳輸速度。 隶後特徵比對模組4〇採用的是支援向量機(jgUpp〇代vect〇r Machine) 系統。特概對模組4〇會將特徵抽取處理模組3〇所抽取的虹膜影像内的 主要特徵賴型資辦5〇⑽所齡的減筆虹膜資料作比對，若比對相 符’則表不使用者身分符合模型資料庫对赫的資料，如此一來，虹膜辨 識系統10即可用來依據不同使用者的虹膜辨識其身份。 相較於先前技術，本發明係利用二值化眼睛影像的方式預先估計瞳孔 位於使用者眼睛影像的估計位置，接下來在從原始的眼睛影像配合瞳孔估 計位置來快速搜尋曈孔的圓心實際位置。之後，由瞳孔圓心的實際位置以 測圓機制找出虹麵域的範I透過上述機制，本發明可以減少搜尋瞳孔 圓心位置的時間’增加虹膜辨識系統辨識正礙生和資料處理效率。這將有 助於未來虹膜辨識系統的商業化使用。 雖然本發明已用較佳實施例揭露如上，然其並非用以限定本發明，任 何熟習此胁者，在*麟本發明之精神和範#可作各種之更動與 修改，因此本發明之保護範圍當視後附之申請專利範圍所界定者為準。” 【圖式簡單說明】 苐1圖係本發明之虹臈辨識系統之功能方塊圖。 17 1335544 第2圖係第1圖之影像擷取裝置之功能方塊圖。 第3圖係第1圖之感像擷取裝置擷取眼睛影像之流程圖。 第4A-4C圖係判斷瞳孔半徑範圍之示意圖。 第5圖係第1圖之影像前置處理模組之功能方塊圖。 第6圖係估計圓心示意圖 第7圖係虹膜正規化之示意圖。 第8圖係影像強化單元執行等化的方法流程圖。 【主要元件符號說明】 10 虹膜辨識系統 50 影像擷取裝置50 20 影像前置處理模組 30 特徵抽取處理模組 40 特徵比對模組 50 模型資料庫 52 第一攝影裝置 54 第二攝影裝置 56 判斷單元 58 調整機構- 55 紅外線投射器 80 區域 32 小波轉換單元 18Rl (0) = \〇PB\ = axcose + ylRs^a2sijie2 In normalization, in each 0 direction, use the ratio of <(0) and £ to map the sum to the relative position in the _ shape. The mapping is for the translation and the (four) circle: the transformation of each point on the second Q is invariant, and the latter is 峨. Because the texture _ in the iris area is small, that is to say, the gray of each pixel of the rainbow _ field will be distributed in the _. _ Touch unit 28 is ___, which makes the probability of occurrence of all grayscale values _. As shown in FIG. 8 , FIG. 8 is a flowchart of a method for performing equalization by the image enhancement unit 28, and the steps are as follows: Step 800: List the gray scale value r/number of the iris region image. Step 802: Count the pixels Km of each gray scale value, / = u ]. Step Xie: Calculate the frequency of occurrence of each gray level of the original image histogram (10), where x is the number of pixels of the iris area image. Step 806: Calculate the cumulative distribution function. Step age fine gi =_55,)+ ()·5] Calculate the gray level A of the mapped input image, i=<U"", p-7, /> is the number of gray levels of the output image, For example, it is an integer symbol. Step 810. Adjust the gray level of the original image with the projection relationship of & && and obtain the output iris image after equalization. Please continue to see the figure. The feature extraction processing module 3A includes a wavelet transform unit 32 for applying the wavelet transform method to extract the main features in the iris image by using the wavelet transform method. Wavelet transform is generally applied to one-dimensional signal processing or two-dimensional image compression. In practice, 1335544 uses wavelet transform to decompose the equalized iris image into two parts: high frequency and low frequency. The high frequency hole number contains edge information or noise, and the low frequency signal approximates the equalized iris image. Therefore, the feature extraction processing module 3 will discard the high frequency signal and leave the low frequency signal to accelerate the transmission speed. The post-feature feature comparison module 4 is a support vector machine (jgUpp〇vect〇r Machine) system. In particular, the module 4 will compare the main features of the iris image extracted by the feature extraction processing module 3〇 with 5减(10) aged iris data, if the comparison matches 'the table' The non-user identity conforms to the data of the model database, so that the iris recognition system 10 can be used to identify the identity of the iris according to different users. Compared with the prior art, the present invention pre-estimates the estimated position of the pupil in the eye image of the user by means of binarizing the eye image, and then quickly searches for the actual position of the center of the pupil from the original eye image with the pupil estimated position. . Then, the actual position of the center of the pupil is determined by the circle-measuring mechanism to find the range of the rainbow surface. Through the above mechanism, the present invention can reduce the time for searching the center of the pupil', increasing the recognition of the iris recognition system and the efficiency of data processing. This will help commercialize the future iris identification system. Although the present invention has been disclosed in the above preferred embodiments, it is not intended to limit the present invention, and various modifications and changes can be made in the spirit and scope of the present invention. This is subject to the definition of the scope of the patent application. BRIEF DESCRIPTION OF THE DRAWINGS [Fig. 1] is a functional block diagram of the rainbow trout identification system of the present invention. 17 1335544 Fig. 2 is a functional block diagram of the image capturing device of Fig. 1. Fig. 3 is a first figure The flow chart of the image capturing device captures the eye image. The 4A-4C figure is a schematic diagram for determining the radius of the pupil. Fig. 5 is a functional block diagram of the image preprocessing module of Fig. 1. Fig. 6 is an estimation Figure 7 of the center of the circle is a schematic diagram of the normalization of the iris. Figure 8 is a flow chart of the method for performing equalization of the image enhancement unit. [Explanation of main component symbols] 10 Iris recognition system 50 Image capture device 50 20 Image pre-processing module 30 Feature Extraction Processing Module 40 Feature Comparison Module 50 Model Library 52 First Photography Device 54 Second Photography Device 56 Judging Unit 58 Adjustment Mechanism - 55 Infrared Projector 80 Region 32 Wavelet Conversion Unit 18