Combining Color and Layout Features for the Identification of Low-resolution Documents

نویسندگان

  • Ardhendu Behera
  • Denis Lalanne
  • Rolf Ingold
چکیده

This paper proposes a method, combining color and layout features, for identifying documents captured from lowresolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. The combined color and layout features are arranged in a symbolic file, which is unique for each document and is called the document’s visual signature. Our identification method first uses the color information in the signatures in order to focus the search space on documents having a similar color distribution, and finally selects the document having the most similar layout structure in the remaining search space. Finally, our experiment considers slide documents, which are often captured using handheld devices. Keywords—Document color modeling, document visual signature, kernel density estimation, document identification.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Color and Layout-Based Identification of Documents Captured from Handheld Devices

This paper proposes a method, combining color and layout features, for identifying documents captured from lowresolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. Our identification method first uses the co...

متن کامل

Identification of Houseplants Using Neuro-vision Based Multi-stage Classification System

In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...

متن کامل

A HYBRID ALGORITHM FOR SIZING AND LAYOUT OPTIMIZATION OF TRUSS STRUCTURES COMBINING DISCRETE PSO AND CONVEX APPROXIMATION

An efficient method for size and layout optimization of the truss structures is presented in this paper. In order to this, an efficient method by combining an improved discrete particle swarm optimization (IDPSO) and method of moving asymptotes (MMA) is proposed. In the hybrid of IDPSO and MMA, the nodal coordinates defining the layout of the structure are optimized with MMA, and afterwards the...

متن کامل

A Deep Model for Super-resolution Enhancement from a Single Image

This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...

متن کامل

Evaluation the Mean Performance and Stability of Lentil Genotypes by Combining Features of AMMI and BLUP Techniques

In this research, 12 selective advanced genotypes of lentil with Kimia and Gachsaran checks were grown for three growing years (2010-2013) in four locations including Gachsaran, Gonbad, Khoramabad and Moghan using randomized complete block design with three replicates in each location. The heatmap plot indicated the variation of seed yield of genotypes in different environments. Mosaic plot sho...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005