圖像分割外文翻譯---一種在線圖像編碼識(shí)別系統(tǒng)的設(shè)計(jì)(存儲(chǔ)版)
【正文】 to right. 3 Preprocessing Image preprocessing includes are: gray image, image noise reduction and enhancement, coding, edge detection, image geometry correction, image coding region of extraction, encoding image binarization, character segmentation, character normalization and so on. Here are some key aspects of the process. gray image processing Images are usually color coded, the actual identification with the image is grayscale, where the need to convert first colorcoded images to grayscale. In the RGB color model, if R = G = B, then color (R, G, B) indicates a Black white color, in which R = G = B is called the value of gray value, gray level processing is to make the color of the R , G, B ponent value equal to the process. Grayscale processing methods are monly used weighted average method, that is, R = G = B = (WRR + WGG + WBB) / 3 Which, WR, WG, WB are the R, G, B the weight of experimental and theoretical proof, when WR = , WG = , WB = , that is when R = G = B = + G + B, can be the most reasonable grayscale. image enhancement processing Direct grayscale transformation ① linear gray level transformation: if the image gray scale is linear, as in the original image f (x, y) grayscale range of [a, b], asked the transformed image intensity range of up to [c, d], According to the linear law, the transformed image g (x, y) as: cyxfab cdyxg ???? ),(),( (1) ② nonlinear transformation log transformation and exponential transformation:When the need to expand low gray zone, gray zone of high pression used on the log transformation, when the need to expand the use of high gray area index transformation. smoothing filter Noise Reduction As the noise in the area corresponding to the edge of the image gray value of such rapid change with a larger part is a high frequency, so the use of lowpass filter (ie, smoothing filter) noise. At the same time can make the image fuzzy smoothing is beneficial to the larger goal of the extraction prior to removal of the smaller details or to target the small interruption link. Smoothing noise reduction method is to use the template on the image convolution operation, linear smoothing filter is the most monly used template is shown in Figure 2 of the 3 3 template, this template and image in pixels by the following method of convolution , get smooth image noise reduction. ① In the figure, roaming the template and the template center and map location of each pixel overlap。 基于特征加權(quán)的模板匹配識(shí)別算法基本思路是：給模板中有字符筆畫的點(diǎn)分配不同的權(quán)重，位 于筆畫中心的點(diǎn)權(quán)重最高，位于筆畫邊緣的點(diǎn)權(quán)重最低，然后將樣本模板與標(biāo)準(zhǔn)模板逐點(diǎn)模糊匹配，按模糊識(shí)別規(guī)則識(shí)別。 字符切割 通過(guò)對(duì)編碼字符區(qū)直接進(jìn)行水平掃描，由字符間距一般可以將字符區(qū)域分割出來(lái)。中值濾波可有效地去除隨機(jī)噪聲，能 得到較好的視覺效果。常用灰度化處理方法是加權(quán)平均值法，即 R=G=B=(WRR+WGG+WBB)/3 其中， WR、 WG、 WB分別是 R、 G、 B 的權(quán)值，實(shí)驗(yàn)和理論證明，當(dāng) WR=, WG=, WB= 時(shí)，即當(dāng) R=G=B=++ 時(shí)，能得到最合理的灰度圖像。 編碼圖像一般都要先轉(zhuǎn)成 BMP 圖像格式，因?yàn)?BMP 格式己經(jīng)成為 PC領(lǐng)域事圖像預(yù)處理 后續(xù)處理 編碼特征提取與識(shí)別 編碼圖像的采集與存儲(chǔ) 實(shí)上的標(biāo)準(zhǔn) —— 幾乎所有為 Windows 操作系統(tǒng)設(shè)計(jì)的 圖像處理軟件都支持這種格式的圖像。 關(guān)鍵詞 ： 圖像處理 。 圖 1 在線圖像編碼字符識(shí)別系統(tǒng)流程圖 在線輪胎圖像編碼字符識(shí)別系統(tǒng)要求對(duì)通過(guò)生產(chǎn)流水線上每一個(gè)輪胎采集含有輪胎編碼的圖像，然后通過(guò)對(duì)圖像的處理，提取出輪胎 編碼特征，采用合適的識(shí)別算法將每一位編碼字符進(jìn)行識(shí)別。下面介紹幾個(gè)關(guān)鍵環(huán)節(jié)的處理過(guò)程。 平滑降噪的方法是使用模板對(duì)圖像進(jìn)行卷積運(yùn)算，線性平滑濾波器最常用的
畢業(yè)設(shè)計(jì)相關(guān)推薦
鄂ICP備17016276號(hào)-1