zeta1999/deslantimg

The deslanting algorithm sets text upright in images. CPU (C++) and GPU (OpenCL) implementation provided.

Deslanting Algorithm

Algorithm removes cursive writing style | Handwritten Text Recognition | C++ | OpenCV | OpenCL

This algorithm sets (handwritten) text in images upright, i.e. it removes the cursive writing style. It is used as a preprocessing step for handwritten text recognition. The following illustration shows input and output of the algorithm for a given image (data/test1.png).

Two implementations are provided:

• CPU: all computations are done on the CPU using OpenCV.
• GPU: each column and shear angle is processed in parallel using OpenCL to compute the optimal shear angle, the remaining work is done on the CPU using OpenCV.

Run demo

Use ./build.sh to build the CPU version or ./build.sh gpu to build the GPU version on Linux using g++. Then, run ./DeslantImg to process the two images provided in the data/ directory (taken from IAM dataset [2]). Two output files should occur in the repositories root directory.

Some notes on how to compile the demo manually and how to compile for Windows or other operating systems:

• Build CPU implementation on Linux (OpenCV must be installed): g++ --std=c++11 src/cpp/main.cpp src/cpp/DeslantImgCPU.cpp `pkg-config --cflags --libs opencv` -o DeslantImg
• If the macro USE_GPU is defined, the computation takes place on the GPU. Build CPU and GPU implementation on Linux (OpenCV and OpenCL must be installed): g++ --std=c++11 -D USE_GPU src/cpp/main.cpp src/cpp/DeslantImgCPU.cpp src/cpp/DeslantImgGPU.cpp src/cpp/CLWrapper.cpp `pkg-config --cflags --libs opencv` -lOpenCL -o DeslantImg
• On Windows, the easiest way is to use Microsoft Visual Studio, put all files into a C++ project, set include and library paths for OpenCV and optionally OpenCL, and finally compile and run the program

Documentation

Call function deslantImg(img, bgcolor) with the input image (grayscale) and the background color (to fill empty image space). It returns the deslanted image computed on the CPU.

#include "DeslantImgCPU.hpp"
...

// read grayscale image
const cv::Mat img = cv::imread("data/test1.png", cv::IMREAD_GRAYSCALE);

// deslant it
const cv::Mat res = htr::deslantImg(img, 255);

// and save the result
cv::imwrite("out1.png", res);

The GPU version additionally takes an instance of CLWrapper which holds all relevant information needed for OpenCL: deslantImg(img, bgcolor, clWrapper). As the construction of a CLWrapper instance takes time, it makes sense to only create one instance and use it for all future calls to deslantImg(img, bgcolor, clWrapper).

#include "DeslantImgGPU.hpp"
...

// read grayscale image
const cv::Mat img = cv::imread("data/test1.png", cv::IMREAD_GRAYSCALE);

// deslant it
htr::CLWrapper clWrapper;
const cv::Mat res = htr::deslantImg(img, 255, clWrapper);

// and save the result
cv::imwrite("out1.png", res);

Algorithm

Vinciarelli and Luettin describe the algorithm in their paper [1]. Here is a short outline of the algorithm:

References

[1] Vinciarelli and Luettin - A new normalization technique for cursive handwritten words

[2] IAM dataset: http://www.fki.inf.unibe.ch/databases/iam-handwriting-database