- Building Computer Vision Projects with OpenCV 4 and C++
- David Millán Escrivá Prateek Joshi Vinícius G. Mendon?a Roy Shilkrot
- 53字
- 2021-07-02 12:28:41
Segmenting our input image
Now, we are going to introduce two techniques to segment our threshold image:
- Connected components
- Find contours
With these two techniques, we are allowed to extract each region of interest (ROI) of our image where our targets objects appear. In our case, these are the nut, screw, and ring.
推薦閱讀
- 在你身邊為你設(shè)計Ⅲ:騰訊服務(wù)設(shè)計思維與實戰(zhàn)
- Python絕技:運用Python成為頂級數(shù)據(jù)工程師
- 劍破冰山:Oracle開發(fā)藝術(shù)
- 輕松學大數(shù)據(jù)挖掘:算法、場景與數(shù)據(jù)產(chǎn)品
- 正則表達式必知必會
- Python廣告數(shù)據(jù)挖掘與分析實戰(zhàn)
- 數(shù)據(jù)化網(wǎng)站運營深度剖析
- 數(shù)據(jù)挖掘原理與SPSS Clementine應(yīng)用寶典
- 數(shù)據(jù)庫技術(shù)實用教程
- 基于OPAC日志的高校圖書館用戶信息需求與檢索行為研究
- SQL優(yōu)化最佳實踐:構(gòu)建高效率Oracle數(shù)據(jù)庫的方法與技巧
- 跨領(lǐng)域信息交換方法與技術(shù)(第二版)
- Oracle 11g+ASP.NET數(shù)據(jù)庫系統(tǒng)開發(fā)案例教程
- The Natural Language Processing Workshop
- 數(shù)據(jù)庫原理與設(shè)計實驗教程(MySQL版)