Scan Tailor - Post-processing tool for Scanned Pages

  •        1775

Scan Tailor is an interactive post-processing tool for scanned pages. It performs operations such as page splitting, deskewing, adding/removing borders, and others. You give it raw scans, and you get pages ready to be printed or assembled into a PDF or DJVU file.

http://scantailor.sourceforge.net
http://sourceforge.net/projects/scantailor/

Tags
Implementation
License
Platform

   




Related Projects

Insight Segmentation and Registration Toolkit

  •    C++

ITK is an open-source, cross-platform system that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and segmenting multidimensional data.

Jimp - An image processing library written entirely in JavaScript for Node

  •    Javascript

An image processing library for Node written entirely in JavaScript, with zero native dependencies. It supports image manipulation methods like Blit an image, Blur an image, Various color manipulation methods, Resize, Scale and Rotate the image, Apply a dither effect to an image, Mask one image with another, Print text onto an image (watermark) and lot more.

zimg - A lightweight and high performance image storage and processing system.

  •    C

Project zimg is a lightweight image storage and processing system. It's written in C and it has high performance in image field. The zimg is designed for high concurrency image server. It supports many features for storing and processing images.The concurrent I/O, distributed storage and in time processing ability of zimg is excellent. You needn't nginx in your image server any more. In the benchmark test, zimg can deal with 3000+ image downloading task per second and 90000+ HTTP echo request per second on a high concurrency level. The performance is higher than PHP or other image processing server. More infomation of zimg is in the documents below.

Marvin - Image Processing Framework

  •    Java

Marvin is an image processing framework that provides features for image and video frame manipulation, multithreading image processing, image filtering and analysis, unit testing, performance analysis and addition of new features via plug-in. It can process camera frames for video filtering, object tracking, augmented reality, motion detection and analysis among other things.

ImageMagick

  •    C++

ImageMagick is a software suite to create, edit, and compose bitmap images. It can read, convert and write images in a variety of formats (over 100) including DPX, EXR, GIF, JPEG, JPEG-2000, PDF, PhotoCD, PNG, Postscript, SVG, and TIFF. Use ImageMagick to translate, flip, mirror, rotate, scale, shear and transform images, adjust image colors, apply various special effects, or draw text, lines, polygons, ellipses and Bézier curves.


imaginary - Fast, simple, stateless HTTP microservice for high-level image processing with first-class support for Docker & Heroku

  •    Go

Fast HTTP microservice written in Go for high-level image processing backed by bimg and libvips. imaginary can be used as private or public HTTP service for massive image processing with first-class support for Docker & Heroku. It's almost dependency-free and only uses net/http native package without additional abstractions for better performance.Supports multiple image operations exposed as a simple HTTP API, with additional optional features such as API token authorization, gzip compression, HTTP traffic throttle strategy and CORS support for web clients.

PyCNN - Image Processing with Cellular Neural Networks in Python

  •    Python

Cellular Neural Networks (CNN) [wikipedia] [paper] are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors. This python library is the implementation of CNN for the application of Image Processing.

GraphicsMagick

  •    C++

GraphicsMagick is the swiss army knife of image processing. It provides a robust and efficient collection of tools and libraries which support reading, writing, and manipulating an image in over 88 major formats including important formats like DPX, GIF, JPEG, JPEG-2000, PNG, PDF, PNM, and TIFF.

bimg - Small Go package for fast high-level image processing powered by libvips C library

  •    Go

Small Go package for fast high-level image processing using libvips via C bindings, providing a simple, elegant and fluent programmatic API.bimg was designed to be a small and efficient library supporting a common set of image operations such as crop, resize, rotate, zoom or watermark. It can read JPEG, PNG, WEBP natively, and optionally TIFF, PDF, GIF and SVG formats if libvips@8.3+ is compiled with proper library bindings.

ruby-vips - Ruby extension for the libvips image processing library.

  •    Ruby

This gem provides a Ruby binding for the libvips image processing library. Programs that use ruby-vips don't manipulate images directly, instead they create pipelines of image processing operations building on a source image. When the end of the pipe is connected to a destination, the whole pipeline executes at once, streaming the image in parallel from source to destination a section at a time.

ruby-vips - Ruby extension for the libvips image processing library.

  •    Ruby

This gem provides a Ruby binding for the libvips image processing library. Programs that use ruby-vips don't manipulate images directly, instead they create pipelines of image processing operations building on a source image. When the end of the pipe is connected to a destination, the whole pipeline executes at once, streaming the image in parallel from source to destination a section at a time.

Scrimage - Scala image processing library

  •    Scala

Scrimage is a consistent, idiomatic, and immutable scala library for manipulating and processing of images. The aim of the this library is to provide a quick and easy way to do the kinds of image operations that are most common, such as scaling, rotating, converting between formats and applying filters. It is not intended to provide functionality that might be required by a more "serious" image processing application - such as face recognition or movement tracking.

vpp - Video++, a C++14 high performance video and image processing library.

  •    C++

The generic container imageNd<V, N> represents a dense N-dimensional rectangle set of pixels with values of type V. For convenience, image1d, image2d, image3d are respectively aliases to imageNd<V, 1>, imageNd<V, 2>, and imageNd<V, 3>. These types provide accesses to the pixel buffer and to other piece of information useful to process the image. In contrast to std::vector, assigning an image to the other does not copy the data, but share them so no accidental expensive deep copy happen.

Simd - C++ image processing library with using of SIMD: SSE, SSE2, SSE3, SSSE3, SSE4

  •    C++

The Simd Library is a free open source image processing library, designed for C and C++ programmers. It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC (big-endian), NEON for ARM.

OTB

  •    C++

The Orfeo Toolbox is a C++ library for high resolution remote sensing image processing. It is developped by CNES in the frame of the ORFEO program. More information is available at www.orfeo-toolbox.org It is based on the medical image processing library ITK and offers particular functionalities for remote sensing image processing in general and for high spatial resolution images in particular. Targeted algorithms for high resolution optical images (SPOT, Quickbird, Worldview, Landsat, Iko

imagej - :sparkler: Open scientific N-dimensional image processing :microscope:

  •    Java

ImageJ is an open source Java image processing program inspired by NIH Image for the Macintosh.

imaging - Simple Go image processing package

  •    Go

Package imaging provides basic image manipulation functions (resize, rotate, flip, crop, etc.). This package is based on the standard Go image package and works best along with it.Image manipulation functions provided by the package take any image type that implements image.Image interface as an input, and return a new image of *image.NRGBA type (32bit RGBA colors, not premultiplied by alpha).

Similar images finder - .NET Image processing in C# and RGB projections

  •    

Start image processing in C# with .NET! This application compares images in a folder (and all subfolders) using RBG projections (horizontal and vertical). I've to optimize it but it's quite fast and the first goal for me is start application for beginners about image processing

bild - A collection of parallel image processing algorithms in pure Go

  •    Go

A collection of parallel image processing algorithms in pure Go.The aim of this project is simplicity in use and development over high performance, but most algorithms are designed to be efficient and make use of parallelism when available. It is based on standard Go packages to reduce dependency use and development abstractions.

lambda-refarch-imagerecognition - The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition

  •    Javascript

The Image Recognition and Processing Backend demonstrates how to use [AWS Step Functions] (https://aws.amazon.com/step-functions/) to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition. This workflow processes photos uploaded to Amazon S3 and extracts metadata from the image such as geolocation, size/format, time, etc. It then uses image recognition to tag objects in the photo. In parallel, it also produces a thumbnail of the photo.This repository contains sample code for all the Lambda functions depicted in the diagram below as well as an AWS CloudFormation template for creating the functions and related resources. There is also a test web app that you can run locally to interact with the backend.