The IIIT 5K-word
2D Box
Classification
OCR/Text Detection
|...
许可协议: Unknown

Overview

The IIIT 5K-word dataset is harvested from Google image search. Query words like billboards, signboard, house numbers, house name plates, movie posters were used to collect images. The dataset contains 5000 cropped word images from Scene Texts and born-digital images. The dataset is divided into train and test parts. This dataset can be used for large lexicon cropped word recognition. We also provide a lexicon of more than 0.5 million dictionary words with this dataset.

Instruction

(Usage: Case insensitive small/medium/large lexicon cropped word recognition)

  1. Open Matlab

  2. Load testdata

  3. A structure testdata will be loaded. This structure has four fields. (a) ImgName The cropped word image name.

    (b) GroundTruth Specifies the ground truth text corresponding to the cropped word (c) smallLexi Contains a lexicon list of 50 words per image (referred to as small size lexicon in the paper) (d) mediumLexi Contains a lexicon list of 1000 words per image (the medium size lexicon)

Citation

If you use this dataset, please cite:

@InProceedings{MishraBMVC12,
  author    = "Mishra, A. and Alahari, K. and Jawahar, C.~V.",
  title     = "Scene Text Recognition using Higher Order Language Priors",
  booktitle = "BMVC",
  year      = "2012",
}
数据概要
数据格式
Image,
数据量
5K
文件大小
100.96MB
发布方
CVIT
CVIT focuses on basic and advanced research in image processing, computer vision, computer graphics and machine learning. This center deals with the generation, processing, and understanding of primarily visual data as well as with the techniques and tools required doing so efficiently. The activity of this center overlaps the traditional areas of Computer Vision, Image Processing, Computer Graphics, Pattern Recognition and Machine Learning. CVIT works on both theoretical as well as practical aspects of visual information processing. Center aims to keep the right balance between the cutting edge academic research and impactful applied research.
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