Target Validation and Image Calibration in
Scanning Systems
COSTIN-ANTON BOIANGIU
Department of Computer Science and Engineering
University “Politehnica” of Bucharest
Splaiul Independentei 313, Bucharest, 060042
ROMANIA
costin.boiangiu@cs.pub.ro
ALEXANDRU VICTOR ŞTEFĂNESCU
Computer Science Department - MS 132
Rice University
PO Box 1892, Houston TX 77251-1892
USA
stefanescu@rice.edu
Abstract: - One of the directions for paper document conservation is conversion to microfilms and scanned
images. Since recently microfilming has been abandoned over digitization, there is a need for standards and
guidelines for the conversion workflow. The article proposes a set of methodologies for calibrating scanning
systems to ensure high quality reproduction of both microfilms and original paper prints, in terms of tonal
reproduction, geometric distortion and image sharpness.
Keywords: Image calibration, sharpness, MTF, tonal reproduction, geometrical distortion, image acquisition
1 Introduction and motivation
Paper documents such as newspapers, books and
other prints suffer in time of various forms of
autonomous decay that can affect paper, among
which are paper acidification and ink and copper
corrosion. In the 1980’s and 1990’s research was
carried out – e.g. the Metamorfoze project in the
Netherlands, a collaborative effort of the Koninklijke
Bibliotheek (National Library) and the Nationaal
Archief (National Archives) – to develop reliable
methods and standards for the conservation of paper
heritage material that was considered of national
importance. The research focused on two directions:
preservation – concerned with slowing down the
decay on the original documents through means of
deacidification, treatment of ink corrosion and
copper corrosion, small repairs, acid-free wrappings
and climatized storage – and conversion – dealing
with the transfer of the threatened material to another
storage medium by means of either microfilming or
digitization.
When research programs
first
started,
microfilming was a reliable method to preserve the
content of an endangered document. However, in
recent years, digitization is preferred over
microfilming, leading to an additional challenge of
converting pre-existing microfilms to digital media,
in order to avoid handling the original documents, an
action which is both costly and potentially damaging
for the decaying prints.
A further direction pursued in recent years is
converting scanned documents (either of the
microfilms or the original paper prints) into
electronic files, especially for large electronic
libraries, for easier access to documents. Content
conversion systems, based on optical character
recognition (OCR), enable operations such as
editing, word searching, easy document storing and
multiplication, and the application of a large set of
text techniques including text-to-speech and text
mining to be performed on the digitalized document.
In addition, this ensures a better preservation of
original documents, due to minimizing the need for
physical use.
Undoubtedly, digitization has many advantages
over microfilming on the access side: digital images
include color reproduction, they allow remote access
and they can be easily searched by using OCR. From
the point of view of preservation, digitization offers
exciting possibilities as well. Since digitized copies
contain color; a high quality digital image is closer
to the original than a microfilm could ever be.
There are nevertheless a number of issues to be
tackled before digitization can definitively be used
as a conversion method for preservation and access.
Standards and guidelines, the workflow, the
metadata, long-term storage and retrieval of digital
images all have to be developed and dealt with.
Scanning system calibration is one of the areas
for which accurate standards and methodologies are
needed. There are many factors which can affect the
scanning quality: defective equipment, variations in
illumination conditions, aging scanner lamps, out-offocus cameras, failing sensors on specific color
channels, etc. This article proposes a set of
methodologies for calibrating scanners to ensure
optimal quality in the digitization of both microfilms
and paper prints, covering the following issues: tonal
reproduction and illumination, color cast and color
accuracy, calibration and tonal reproduction, image
sharpness and optical distortion.
2 Target Validation
Scanner calibration is performed using special
technical targets. Target validation refers to the
process of checking if certain parameters of the
scanned images of the targets verify some predefined
standards. There are two kinds of technical targets:
targets that must be captured with every individual
image that is made from an original, and technical
target sheets that must be captured for every batch (a
specified number of images) or for a series of images
made in a specified period of time (for instance one
morning or afternoon) [5].
2.1 Initial Setup
The monitor settings (e.g. white point 6500K,
gamma 2.2, gray desktop background, etc.),
workspace conditions (e.g. ambient illumination 3264 lux, color temperature 5000K, neutral ambient
colors, etc.) and scanning procedure should match
the requirements mentioned in the Metamorfoze
project guidelines [5]. The aim of these standards is
to remove any effects interfering with the subjective,
visual assessment of the images, and to support
uniformity in assessment between supplier and
client.
2.2 Target Sheet Composition and Sequence
All aspects are assessed by capturing images of a
frame-filling white sheet of cardboard on top of
which various technical targets are placed. The
optical density of the white cardboard must be
between 0.05 and 0.15 [5]. For all target sheets, the
distance between them and the lens must be equal to
the distance between the original and the lens. In
other words: the reduction factor used for capturing
the target sheets much be equal to the reduction
factor used for capturing the originals.
The following four target sheets are used in
sequence for evaluating document scanning
performance:
First target sheet: tonal reproduction and
illumination. Both aspects are assessed with the aid
of one single image, which is constructed by
centering a Kodak Gray Scale (see Fig. 1) at the
bottom of the cardboard sheet.
Fig. 1. Kodak Gray Scale
Second target sheet: color cast and color
accuracy. The two aspects are evaluated using a
target sheet similar to the first, but with a color test
target, the GretagMacbeth Color Checker SG (see
Fig. 2), positioned in the center of the sheet.
Fig. 2. GretagMacbeth Color Checker SG: front, back and legend
Third target sheet: sharpness. Again, the target
sheet is based on the first type, this time with five
QA-62 slanted edge sharpness test targets (see Fig.
3) placed in the center and the four corners of the
target sheet.
Fig. 3. 5 x QA-62 targets plus Tiffen grayscale
Fig. 4. QA-2 metric test target
Fourth target sheet: optical distortion. The target
sheet is constructed by placing a QA-2 metric test
target (see Fig. 4) containing length markers in the
center of the white cardboard.
For assessing microfilm scanning performance, a
Microfilm target sheet is used. It contains all test
targets from the four document scanning sheets
placed on a single cardboard base. All aspects are
evaluated by studying the scanned image of the
target sheet captured on microfilm.
For every individual image, it must be possible to
assess tonal reproduction and color accuracy in
relation to the original. Therefore a Kodak Gray
Scale Q-13 or Q-14 and a mini GretagMacbeth Color
Checker Rendition Chart must be captured together
with every single original [5]. Both technical targets
must be positioned side by side, and clearly visible,
centered at the bottom of the frame.
How to enable assessment of color cast for each
individual image is still being investigated [3]. A
possible solution might be to use a target with a
number of neutral gray patches, placed in a right
angle. This target could be positioned in each corner,
and captured with each image.
The following sections discuss the methodology
of evaluating each aspect in the scanning process.
The proposed method is an improved version of
the slanted edge method described in the ISO 12233
methodology and the SAFECOM methods [4]. The
slanted edge method involves the analysis of a potion
of an image containing an edge slightly tilted with
respect to the detector and, compared to other
methods, has the advantage of requiring a small
number of pixels from a single image to be
processed.
6. Sharpness Validation Methodology
3. Tonal Reproduction and
Illumination
Measured on the basis of the Kodak Gray Scale (Q13
or Q14) all patches of the Kodak Gray Scale should
be distinguishable from each other. The pixel value
of patch A has to be between 250-230. The pixel
value of patch 19 must be above 10. The pixel value
should be measured with a 5x5 average window. For
noise test acceptance within the pixel values of the
Kodak Gray Scale (or equivalent) a maximum
standard deviation of 10 is allowed.
4. Color Cast and Color Accuracy
The color cast is determined by measuring the
grayscale patches of the GretagMacbeth Color
Checker within a 5x5 average window. The patches
must be neutral. The maximum deviation allowed is 4 or +4 pixel point difference between the RGB
channels for every patch, when taking the middle
RGB-value as a starting point.
This section details a methodology suitable for
calibrating document or microfilm scanning
equipment with respect to the image sharpness
quality factor.
6.1 Initial Setup
For measuring image sharpness, a special target shall
be constructed, containing five calibration targets
(four near the corners and one in the center) such as
the QA-62 target (presented in Fig. 5) with four
slanted edges as sides of a rectangle. The target must
be scanned and validated at regular intervals (e.g. at
the beginning of the day) or after any change in
scanning parameters (e.g. resolution, scaling factor
for microfilms, etc.).
5. Image Sharpness Assessment
The sharpness of a photographic imaging system or
of a component of the system (lens, film, image
sensor, scanner, enlarging lens, etc.) is a quality
factor that determines the amount of detail that can
be reproduced. It is characterized by a parameter
called Modulation Transfer Function (MTF), also
known as spatial frequency response, which is a
measure of the response of an optical system to
varying intensities of light. The MTF is strictly the
response to parallel lines whose brightness varies
from minimum to maximum in a sinusoidal function.
Traditional methods for MTF measurements were
initially designed for devices forming continuous
images and can produce erroneous results, because
the sampling of digital devices is not properly taken
into consideration [1]. Additionally, MTF results can
depend on the chosen technique (sine target or bar
target utilization, slit or knife-edge technique).
Fig. 5. Quality Assurance 62 sharpness calibration
target
6.2 Detecting the Region of Interest
Automated sharpness validation techniques can be
applied on the scanned target. To detect the five
slanted rectangles in the target image, a conversion
to black-and-white followed by 4-connected (black)
pixel detection can be applied. By analyzing the
shape of the connected regions, the rectangles can
recognized and their slant angles can be checked to
meet certain limits (e.g. between 2 and 5 degrees).
For each of the five rectangles, image sharpness
shall be measured by processing the pixels contained
in four regions of interest (RoI), corresponding to the
slanted edges of the rectangle. The RoI is required to
be of a minimum size of 80 by 60 pixels (see Fig. 6)
and is normally selected by dividing the minimal
non-slanted rectangle surrounding each slanted
rectangle into 6 parts, both horizontally and
vertically, and extracting 4/6 by 1/6 portions (e.g. for
the top edge, the RoI is situated in the top sixth and
middle four sixths of the reference rectangle).
horizontal Spatial Frequency Response (SFR) of the
detector.
The ESF must be resampled to a fixed interval by
accumulating the projected pixels into “bins” having
the width a fraction of the pixel pitch. This can be
achieved by filtering the pixel values with a triangle
filter of unit height and the width of a bin. Thus, the
value associated to each bin is the weighted average
of the pixels filtered by the triangle function centered
in the bin. This allows analysis of spatial frequencies
beyond the normal Nyquist frequency [4]. The
number of bins per pixel distance is usually chosen
as 4. Higher values may lead to insufficiently
populated or empty bins.
Fig. 6. Best minimum cropped region of slanted
edge
6.3
Modulation
Computation
Transfer
Function
The algorithm for computing the MTF and the
associated frequency response graph is derived from
the International Standard 12233 [4]. The following
steps are performed for each RoI of each QA-62
target and, depending on the employed scanning
color space, for each RGB color channel plus
combined luminance channel (Y = 0.299 × Red +
0.587 × Green + 0.114 × Blue) for document scans,
or just the gray channel for grayscale microfilm
scans:
For each pixel column in the RoI (which is
rotated to the position corresponding to the top edge
RoI, for reference purposes) the position of the
separation line between the background and the
slanted rectangle is determined by maximizing the
difference of the sum of weighted pixel values on the
two sides of a triangle filter of predefined width (e.g.
10 pixels) sliding over the pixels in the column.
The least-squares fit line through the coordinates
found at point (1) is determined and is used to
approximate the separation border between the
background and the slanted rectangle.
Pixels in the RoI no further than a predetermined
distance (normally 1mm, around 12 pixels at
300DPI) from the fitted line, on both sides, are
projected along the edge transition, resulting in
distance-color tuples. These values represent the
Edge Spread Function (ESF) which is the system
response to the input of an ideal edge [2]. The ESF is
super-sampled because of the slanted edge which
induces differences in the sub-pixel location of the
projected pixels onto the perpendicular. A vertically
oriented edge would only allow obtaining the
Fig. 7. (a) ESF, (b) LSF, (c) Hamming LSF, (d) MTF
plots
The equally spaced ESF samples obtained at (4)
are derived (d/dx) in order to obtain the Line Spread
Function (LSF). A Hamming windowing function is
applied to force the derivative to zero at the
endpoints [4], reducing the effects of the Gibbs
phenomenon that results from truncation of an
infinite series [1].
The normalized magnitude of a linear Fast
Fourier Transform performed on the LSF yields the
MTF (see Fig. 7).
Care must be taken in selecting the number of
points calculated along the ESF with respect to the
sampling rate in order to obtain the desired number
of points in the resulting MTF. The frequency axis of
the MTF must be scaled to represent the calculated
MTF in terms of the Nyquist frequency of the
imaging system, defined as the highest sinusoidal
frequency that can be represented by a sampled
signal and is equal to one half the sampling rate of
the system [2] – always 0.5 cycles per pixel.
For
maximum
precision
in
sharpness
measurement, steps (3) to (6) in the MTF
computation algorithm can be repeated for the
interpolated line at step (2) rotated by slight angles in
steps of ±0.1 degrees, taking into consideration only
the MTF curve with the highest values.
6.4 Sharpness Specification
For a scanning system to pass sharpness validation
certain criteria must be defined. Relevant indications
are found by checking the frequency at which the
MTF graph drops to 10% of its initial, zero
frequency value. Values above 70% of the Nyquist
frequency
are
desirable.
The
frequency
corresponding to half the maximum MTF value
(MTF50P) is also a good sharpness metric.
Furthermore, internal sharpening (performed by
firmware in scanning equipment) can be detected by
comparing the peak MTF value with the initial value.
A ratio below 1.2 is acceptable [5].
7. Optical Distortions
The allowed deviation is a change in length or height
of 1% at the most. The Image Evaluation Test Target
(QA-2) must be used. The size of this target is A3.
To measure larger sizes, a larger test target must be
used.
8. Conclusions
Digitalization is the future for the preservation of
information contained in decaying paper prints.
Detailed methodologies for calibration of scanning
equipment are required to avoid geometric and color
distortions, as well as ensuring a level of high image
sharpness. The paper presented a methodology and
an algorithm to assess sharpness based on the
Modulation Transfer Function of the scanning
system.
References:
[1] [1] Magali Estribeau ; Pierre Magnan, Fast
MTF measurement of CMOS imagers using
ISO 12233 slanted-edge methodology,
Proceedings of SPIE, Vol 5251, 2004
[2] [2] Kohm, K. Modulation Transfer Function
Measurement Method and Results For the
Orbview-3 High Resolution Imaging
Satellite, Proceedings of ISPRS XXXV,
Istanbul, July 2004, pp. 7-12
[3] [3] McCamy, C.S., Marcus, H., and
Davidson, J.G., A Color Rendition Chart,
Journal
of
Applied
Photographic
Engineering 11(3) (Summer issue, 1976), pp.
95-99.
[4] [4] SAFECOM. Public Safety Statement of
Requirements for Communications &
Interoperability, The SAFECOM Program
Department of Homeland Security, pg.99103, Vol II, version 1.0, August 2006
[5] [5] Metamorfoze. Metamorfoze Preservation
Imaging
Guidelines,
Koninklijke
Bibliotheek: National Library of the
Netherlands, The Hague, June 2007