Abstract book (pdf) - ICPR 2010

09:00-11:10, Paper WeAT8.56
Enhancing the Filtering-out of the Back-to-Front Interference in Color Documents with a Neural Classifier
Silva, Gabriel De França Pereira E, Univ. Federal de Pernambuco
Lins, Rafael Dueire, Univ. Federal de Pernambuco
Silva, João Marcelo Monte Da, Univ. Federal de Pernambuco
Banergee, Serene, Hewlett-Packard Labs - India
Kuchibhotla, Anjaneyulu, Hewlett-Packard Labs - India
Thielo, Marcelo, Hewlett-Parckard Labs - Brazil
Back-to-front, show-through, or bleeding are the names given to the interference that appears whenever one writes or
prints on both sides of translucent paper. Such interference degrades image binarization and document transcription via
OCR. The technical literature presents several algorithms to remove the back-to-front noise, but no algorithm is good
enough in all cases. This article presents a new technique to remove such noise in color documents which makes use of
neural classifiers to evaluate the degree of intensity of the interference and besides that to indicate the existence of blur.
Such classifier allows tuning the parameters of an algorithm for back-to-front interference and document enhancement.
09:00-11:10, Paper WeAT8.57
A Scale Estimation Algorithm using Phase-Based Correspondence Matching for Electron Microscope Images
Suzuki, Ayako, Tohoku Univ.
Ito, Koichi, Tohoku Univ.
Aoki, Takafumi, Tohoku Univ.
Tsuneta, Ruriko, Hitachi, Ltd., Central Res. Lab.
This paper proposes a multi-stage scale estimation algorithm using phase-based correspondence matching for electron
microscope images. Consider a sequence of microscope images of the same target object, where the image magnification
is gradually increased so that the final image has a very large scale factor S (e.g., S=1,000) with respect to the initial image.
The problem considered in this paper is to estimate the overall scale factor S of the given image sequence. The proposed
scale estimation technique provides a new methodology for high-accuracy magnification calibration of electron microscopes.
Experimental evaluation using Mandelbrot images as precisely scale-controlled image sequence shows that the
proposed method can estimate the scale factor S=1,000 with approximately 0.1%-scale error. This paper also describes an
application of the proposed algorithm to the magnification calibration of an actual STEM (Scanning Transmission Electron
Microscope).
09:00-11:10, Paper WeAT8.58
Edge Drawing: An Heuristic Approach to Robust Real-Time Edge Detection
Topal, Cihan, Anadolu Univ.
Akinlar, Cuneyt, Anadolu Univ.
Genc, Yakup, Siemens Corp. Res.
We propose a new edge detection algorithm that works by computing a set of anchor edge points in an image and then
linking these anchor points by drawing edges between them. The resulting edge map consists of perfect contiguous, one
pixel wide edges. The performance tests show that our algorithm is up to 16% faster than the fastest known edge detection
algorithm, i.e., OpenCV implementation of the Canny edge detector. We believe that our edge detector is a novel step in
edge detection and would be very suitable for the next generation real-time image processing and computer vision applications.
09:00-11:10, Paper WeAT8.59
MPEG-2 Video Watermarking using Pattern Consideration
Mansouri, Azadeh, Shahid Beheshti Univ.
Mahmoudi Aznaveh, Ahmad, Shahid Beheshti Univ.
Torkamani-Azar, Farah, Shahid Beheshti Univ.
This paper proposes a new method for digital video watermarking in compressed domain. Both the embedding and extracting
phases are performed after entropy decoding. Consequently, fully decompressing the compressed video is not
necessary making this scheme an appropriate choice for real-time application. Furthermore, taking the structural information
into account leads to presenting a robust watermarking scheme along with less quality degradation. To select suitable
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