ocr

Cleaning image for OCR

可紊 提交于 2020-03-10 14:41:20
问题 I've been trying to clear images for OCR: (the lines) I need to remove these lines to sometimes further process the image and I'm getting pretty close but a lot of the time the threshold takes away too much from the text: copy = img.copy() blur = cv2.GaussianBlur(copy, (9,9), 0) thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,30) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9)) dilate = cv2.dilate(thresh, kernel, iterations=2) cnts =

Cleaning image for OCR

吃可爱长大的小学妹 提交于 2020-03-10 14:37:11
问题 I've been trying to clear images for OCR: (the lines) I need to remove these lines to sometimes further process the image and I'm getting pretty close but a lot of the time the threshold takes away too much from the text: copy = img.copy() blur = cv2.GaussianBlur(copy, (9,9), 0) thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,30) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9)) dilate = cv2.dilate(thresh, kernel, iterations=2) cnts =

Cleaning image for OCR

时光毁灭记忆、已成空白 提交于 2020-03-10 14:36:00
问题 I've been trying to clear images for OCR: (the lines) I need to remove these lines to sometimes further process the image and I'm getting pretty close but a lot of the time the threshold takes away too much from the text: copy = img.copy() blur = cv2.GaussianBlur(copy, (9,9), 0) thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,30) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9)) dilate = cv2.dilate(thresh, kernel, iterations=2) cnts =

Cleaning image for OCR

十年热恋 提交于 2020-03-10 14:35:30
问题 I've been trying to clear images for OCR: (the lines) I need to remove these lines to sometimes further process the image and I'm getting pretty close but a lot of the time the threshold takes away too much from the text: copy = img.copy() blur = cv2.GaussianBlur(copy, (9,9), 0) thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,30) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9)) dilate = cv2.dilate(thresh, kernel, iterations=2) cnts =

浅谈OCR之Tesseract

别等时光非礼了梦想. 提交于 2020-03-08 15:04:26
光 学字符识别(OCR,Optical Character Recognition)是指对文本资料进行扫描,然后对图像文件进行分析处理,获取文字及版面信息的过程。OCR技术非常专业,一般多是印刷、打印行业 的从业人员使用,可以快速的将纸质资料转换为电子资料。关于中文OCR,目前国内水平较高的有清华文通、汉王、尚书,其产品各有千秋,价格不菲。国外 OCR发展较早,像一些大公司,如IBM、微软、HP等,即使没有推出单独的OCR产品,但是他们的研发团队早已掌握核心技术,将OCR功能植入了自身的 软件系统。对于我们程序员来说,一般用不到那么高级的,主要在开发中能够集成基本的OCR功能就可以了。这两天我查找了很多免费OCR软件、类库,特地整 理一下,今天首先来谈谈Tesseract,下一次将讨论下Onenote 2010中的OCR API实现。可以在 这里 查看OCR技术的发展简史。 测试代码下载 转载请注明出处: http://www.cnblogs.com/brooks-dotnet/archive/2010/10/05/1844203.html 1、Tesseract概述 Tesseract的OCR引擎最先由HP实验室于1985年开始研发,至1995年时已经成为OCR业内最准确的三款识别引擎之一。然而,HP不久便决定放弃OCR业务,Tesseract也从此尘封。 数年以后,HP意识到

集成利用tesseract.exe进行ocr

给你一囗甜甜゛ 提交于 2020-03-08 15:02:52
ocr是一个宽泛的概念。市场上面ocr将一直是一个不断发展、需求强烈的方向。 我认为,从难度上区分,中文ocr难于英文ocr;手写ocr难于印刷ocr。所以两两组合,中文手写体最难(比如毛体,有一些人都识别不了);而英文(数字)印刷体ocr最简单,对于最简单的东西,我认为就可以直接使用tesseract,它本身就是集成了对英文(数字)的识别。将这个功能集成起来,甚至是研究其开源实现,将其融合起来。 下载http://uniontesting.com/thread-32030-1-1.html 比较详细的介绍来自于:http://www.cnblogs.com/brooks-dotnet/archive/2010/10/05/1844203.html 如果采用命令行的方式集成,核心代码,可以达到一定的效果: private void button1_Click(object sender, EventArgs e) { string filePath = @"tesseract.exe"; string paramstr = @"bbb3.jpg r"; System.Diagnostics.Process.Start(filePath,paramstr); } 通过 http://blog.csdn.net/fengbingchun/article/details

IT行业新名词--透明手机/OCR(光学字符识别)/夹背电池

大兔子大兔子 提交于 2020-03-08 14:16:31
透明手机 机身设计的一大关键部分是可替换玻璃的使用,利用导电技术,在看不到线路的环境下,让LED发光。 这样的玻璃内含液晶分子,对于内容的显示则是通过电流对分子的刺激来实现。当手机断电后,分子位置会随机分布,并呈现出乳白色的外观。 透明手机的设计特点概括起来有: 1、体积小。厚度约0.5公分,和iPhone5相比,屏幕4.3英寸,重量轻25%。 2、强化防摔,即使重重的摔在地上也不会支离破碎。 3、单面触控,但能双面显示。 4、电池、麦克风和microSD卡槽都位于手机的底部,这些部件因暂无法实现透明化而被覆盖起来。 OCR (Optical Character Recognition,光学字符识别) 是指电子设备(比如扫描仪或数码相机)检查纸上打印的字符,通过检測暗、亮的模式确定其形状,然后用字符识别方法将形状翻译成计算机文字的过程;即,对文本资料进行扫描,然后对图像文件进行分析处理,获取文字及版面信息的过程。怎样除错或利用辅助信息提高识别正确率,是OCR最重要的课题,ICR(Intelligent Character Recognition)的名词也因此而产生。衡量一个OCR系统性能好坏的主要指标有:拒识率、误识率、识别速度、用户界面的友好性,产品的稳定性,易用性及可行性等。这也就是能够将PDF转换为Word文档的工作原理。 夹背电池 也叫“外置电池”、“后备电池”、

Clean text images with OpenCV for OCR reading

核能气质少年 提交于 2020-03-05 04:33:28
问题 I received some images that need to be treated in order to OCR some information out of them. Here are the originals: original 1 original 2 original 3 original 4 After processing them with this code: img = cv2.imread('original_1.jpg', 0) ret,thresh = cv2.threshold(img,55,255,cv2.THRESH_BINARY) opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, cv2.getStructuringElement(cv2.MORPH_RECT,(2,2))) cv2.imwrite('result_1.jpg', opening) I get these results: result 1 result 2 result 3 result 4 As you

Tesseract: Differing output / How do I find out which parameters are being used on a given run?

妖精的绣舞 提交于 2020-03-04 23:04:57
问题 Consider this small png image depicting the word 'Account' in black on a white background: For this ground-truth image the output differs between the following two Tesseract command-line operations, with (A) better than (B). (B) is required in order for me as the user to be have any hope of controlling Tesseract's some 660 configuration parameters - but at (A)'s extraction performance. Case A (no config file): tesseract -v test.png test tesseract 4.1.0 leptonica-1.78.0 libgif 5.1.4 : libjpeg

c# Bitmap.Save A generic error occurred in GDI+ windows application

房东的猫 提交于 2020-03-04 05:53:07
问题 I am doing OCR application. I have this error when I run the system which the system will save the picturebox3.image into a folder. //When user is selecting, RegionSelect = true private bool RegionSelect = false; private int x0, x1, y0, y1; private Bitmap bmpImage; private void loadImageBT_Click(object sender, EventArgs e) { try { OpenFileDialog open = new OpenFileDialog(); open.InitialDirectory = @"C:\Users\Shen\Desktop"; open.Filter = "Image Files(*.jpg; *.jpeg)|*.jpg; *.jpeg"; if (open