Abstract: Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Abstract: Texture classification is an important image processing
task with a broad application range. Many different techniques for
texture classification have been explored. Using sparse approximation
as a feature extraction method for texture classification is a relatively
new approach, and Skretting et al. recently presented the Frame
Texture Classification Method (FTCM), showing very good results on
classical texture images. As an extension of that work the FTCM is
here tested on a real world application as detection of abnormalities
in mammograms. Some extensions to the original FTCM that are
useful in some applications are implemented; two different smoothing
techniques and a vector augmentation technique. Both detection of
microcalcifications (as a primary detection technique and as a last
stage of a detection scheme), and soft tissue lesions in mammograms
are explored. All the results are interesting, and especially the results
using FTCM on regions of interest as the last stage in a detection
scheme for microcalcifications are promising.
Abstract: The recent growth of using multimedia transmission
over wireless communication systems, have challenges to protect the
data from lost due to wireless channel effect. Images are corrupted
due to the noise and fading when transmitted over wireless channel,
in wireless channel the image is transmitted block by block, Due to
severe fading, entire image blocks can be damaged. The aim of this
paper comes out from need to enhance the digital images at the
wireless receiver side. Proposed Boundary Interpolation (BI)
Algorithm using wavelet, have been adapted here used to
reconstruction the lost block in the image at the receiver depend on
the correlation between the lost block and its neighbors. New
Proposed technique by using Boundary Interpolation (BI) Algorithm
using wavelet with Pixel interleaver has been implemented. Pixel
interleaver work on distribute the pixel to new pixel position of
original image before transmitting the image. The block lost through
wireless channel is only effects individual pixel. The lost pixels at the
receiver side can be recovered by using Boundary Interpolation (BI)
Algorithm using wavelet. The results showed that the New proposed
algorithm boundary interpolation (BI) using wavelet with pixel
interleaver is better in term of MSE and PSNR.
Abstract: In this paper we present a novel approach for wavelet compression of electrocardiogram (ECG) signals based on the set partitioning in hierarchical trees (SPIHT) coding algorithm. SPIHT algorithm has achieved prominent success in image compression. Here we use a modified version of SPIHT for one dimensional signals. We applied wavelet transform with SPIHT coding algorithm on different records of MIT-BIH database. The results show the high efficiency of this method in ECG compression.
Abstract: A new blind gray-level watermarking scheme is described. In the proposed method, the host image is first divided into 4*4 non-overlapping blocks. For each block, two first AC coefficients of its Hadamard transform are then estimated using DC coefficients of its neighbor blocks. A gray-level watermark is then added into estimated values. Since embedding watermark does not change the DC coefficients, watermark extracting could be done by estimating AC coefficients and comparing them with their actual values. Several experiments are made and results suggest the robustness of the proposed algorithm.
Abstract: In this study, a system of encryption based on chaotic
sequences is described. The system is used for encrypting digital
image data for the purpose of secure image transmission. An image
secure communication scheme based on Logistic map chaotic
sequences with a nonlinear function is proposed in this paper.
Encryption and decryption keys are obtained by one-dimensional
Logistic map that generates secret key for the input of the nonlinear
function. Receiver can recover the information using the received
signal and identical key sequences through the inverse system
technique. The results of computer simulations indicate that the
transmitted source image can be correctly and reliably recovered by
using proposed scheme even under the noisy channel. The
performance of the system will be discussed through evaluating the
quality of recovered image with and without channel noise.
Abstract: In this paper we present a photo mosaic smartphone
application in client-server based large-scale image databases. Photo
mosaic is not a new concept, but there are very few smartphone
applications especially for a huge number of images in the
client-server environment. To support large-scale image databases,
we first propose an overall framework working as a client-server
model. We then present a concept of image-PAA features to efficiently
handle a huge number of images and discuss its lower bounding
property. We also present a best-match algorithm that exploits the
lower bounding property of image-PAA. We finally implement an
efficient Android-based application and demonstrate its feasibility.
Abstract: In this paper we have proposed three and two
stage still gray scale image compressor based on BTC. In our
schemes, we have employed a combination of four techniques
to reduce the bit rate. They are quad tree segmentation, bit
plane omission, bit plane coding using 32 visual patterns and
interpolative bit plane coding. The experimental results show
that the proposed schemes achieve an average bit rate of 0.46
bits per pixel (bpp) for standard gray scale images with an
average PSNR value of 30.25, which is better than the results
from the exiting similar methods based on BTC.
Abstract: This paper includes two novel techniques for skew
estimation of binary document images. These algorithms are based on
connected component analysis and Hough transform. Both these
methods focus on reducing the amount of input data provided to
Hough transform. In the first method, referred as word centroid
approach, the centroids of selected words are used for skew detection.
In the second method, referred as dilate & thin approach, the selected
characters are blocked and dilated to get word blocks and later
thinning is applied. The final image fed to Hough transform has the
thinned coordinates of word blocks in the image. The methods have
been successful in reducing the computational complexity of Hough
transform based skew estimation algorithms. Promising experimental
results are also provided to prove the effectiveness of the proposed
methods.
Abstract: The purpose of this study is to research on thoughts transmitted from virtual fitting-room and to deduce discussion in an auxiliary narrative way. The research structure is based on 3D virtual fitting-room as the research subject. Initially, we will discuss the principles of narrate study, User Demand and so on by using a narrative design pattern to transmit their objective indications of “people-situation-reason-object", etc, and then to analyze the virtual fitting-room examples that are able to provide a new thinking for designers who engaged in clothing related industry – which comes in “story telling" and “user-centered design" forms. Clothing designs are not just to cover up the body to keep warm but to draw closer to people-s demand physiologically and psychologically through interactive designs so as to achieve cognition between people and environment. In the “outside" goal of clothing-s functional designs, we use tribal group-s behavior characteristics to “transform" the existing personal cultural stories, and “reform" them to design appropriate interactive products. Synthesizing the above matters, apart from being able to regard “narrate" as a kind of functional thinking process, we are also able to regard it as a kind of choice, arrangement and an activity of story expression, allowing interactive design-s spirit, product characteristics and experience ideas be transmitted to target tribal group in a visual image performance method. It is a far more confident and innovative attempt, and meanwhile, able to achieve entertainment, joyful and so forth fundamental interactive transmissions. Therefore, this study takes “user-centered design" thinking as a basis to establish a set of clothing designs with interactive experience patterns and to assist designers to examine the five sensual feeling of interactive demands in order to initiate a new value in textile industry.
Abstract: In the last decade digital watermarking procedures have
become increasingly applied to implement the copyright protection
of multimedia digital contents distributed on the Internet. To this
end, it is worth noting that a lot of watermarking procedures
for images and videos proposed in literature are based on spread
spectrum techniques. However, some scepticism about the robustness
and security of such watermarking procedures has arisen because
of some documented attacks which claim to render the inserted
watermarks undetectable. On the other hand, web content providers
wish to exploit watermarking procedures characterized by flexible and
efficient implementations and which can be easily integrated in their
existing web services frameworks or platforms. This paper presents
how a simple spread spectrum watermarking procedure for MPEG-2
videos can be modified to be exploited in web contexts. To this end,
the proposed procedure has been made secure and robust against some
well-known and dangerous attacks. Furthermore, its basic scheme
has been optimized by making the insertion procedure adaptive with
respect to the terminals used to open the videos and the network transactions
carried out to deliver them to buyers. Finally, two different
implementations of the procedure have been developed: the former
is a high performance parallel implementation, whereas the latter is
a portable Java and XML based implementation. Thus, the paper
demonstrates that a simple spread spectrum watermarking procedure,
with limited and appropriate modifications to the embedding scheme,
can still represent a valid alternative to many other well-known and
more recent watermarking procedures proposed in literature.
Abstract: This paper presents an effective traffic lights detection
method at the night-time. First, candidate blobs of traffic lights are
extracted from RGB color image. Input image is represented on the
dominant color domain by using color transform proposed by Ruta,
then red and green color dominant regions are selected as candidates.
After candidate blob selection, we carry out shape filter for noise
reduction using information of blobs such as length, area, area of
boundary box, etc. A multi-class classifier based on SVM (Support
Vector Machine) applies into the candidates. Three kinds of features
are used. We use basic features such as blob width, height, center
coordinate, area, area of blob. Bright based stochastic features are also
used. In particular, geometric based moment-s values between
candidate region and adjacent region are proposed and used to improve
the detection performance. The proposed system is implemented on
Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the
urban and rural road videos. Through the test, we show that the
proposed method using PF, BMF, and GMF reaches up to 93 % of
detection rate with computation time of in average 15 ms/frame.
Abstract: The scattering effect of light in fog improves the
difficulty in visibility thus introducing disturbances in transport
facilities in urban or industrial areas causing fatal accidents or public
harassments, therefore, developing an enhanced fog vision system
with radio wave to improvise the way outs of these severe problems
is really a big challenge for researchers. Series of experimental
studies already been done and more are in progress to know the
weather effect on radio frequencies for different ranges. According to
Rayleigh scattering Law, the propagating wavelength should be
greater than the diameter of the particle present in the penetrating
medium. Direct wave RF signal thus have high chance of failure to
work in such weather for detection of any object. Therefore an
extensive study was required to find suitable region in the RF band
that can help us in detecting objects with proper shape. This paper
produces some results on object detection using 912 MHz band with
successful detection of the persistence of any object coming under the
trajectory of a vehicle navigating in indoor and outdoor environment.
The developed images are finally transformed to video signal to
enable continuous monitoring.
Abstract: This paper starts with a critical view of beautiful female images in the mass media being frequently generated by a stereotypical Korean concept of beauty. Several female beauty myths have evolved in Korea during the present decade. Nearly all of them have formed due to a deeply-ingrained androcentric ideology which objectifies women. Mass media causes the public to hold a distorted concept about female beauty. There is a huge gap between women in reality and representative women in the mass media. It is essential to have an unbiased perception of female images presented in the mass media. Due to cosmetic advertisements projecting contemporary images of female beauty to promote products, cosmetics images will be examined in regard to female beauty myths portrayed by the mass media. This paper will analyze features of female beauty myths in Korea and their intrinsic characteristics.
Abstract: This paper aims to present a survey of object
recognition/classification methods based on image moments. We
review various types of moments (geometric moments, complex
moments) and moment-based invariants with respect to various
image degradations and distortions (rotation, scaling, affine
transform, image blurring, etc.) which can be used as shape
descriptors for classification. We explain a general theory how to
construct these invariants and show also a few of them in explicit
forms. We review efficient numerical algorithms that can be used
for moment computation and demonstrate practical examples of
using moment invariants in real applications.
Abstract: This paper proposes an efficient method to classify
inverse synthetic aperture (ISAR) images. Because ISAR images can
be translated and rotated in the 2-dimensional image place, invariance
to the two factors is indispensable for successful classification. The
proposed method achieves invariance to translation and rotation of
ISAR images using a combination of two-dimensional Fourier
transform, polar mapping and correlation-based alignment of the
image. Classification is conducted using a simple matching score
classifier. In simulations using the real ISAR images of five scaled
models measured in a compact range, the proposed method yields
classification ratios higher than 97 %.
Abstract: In this paper a new concept of partial complement of a graph G is introduced and using the same a new graph parameter, called completion number of a graph G, denoted by c(G) is defined. Some basic properties of graph parameter, completion number, are studied and upperbounds for completion number of classes of graphs are obtained , the paper includes the characterization also.
Abstract: In a handwriting recognition problem, characters can
be represented using chain codes. The main problem in representing
characters using chain code is optimizing the length of the chain
code. This paper proposes to use randomized algorithm to minimize
the length of Freeman Chain Codes (FCC) generated from isolated
handwritten characters. Feedforward neural network is used in the
classification stage to recognize the image characters. Our test results
show that by applying the proposed model, we reached a relatively
high accuracy for the problem of isolated handwritten when tested on
NIST database.
Abstract: In this paper we proposed a novel method to acquire
the ROI (Region of interest) of unsupervised and touch-less palmprint
captured from a web camera in real-time. We use Viola-Jones
approach and skin model to get the target area in real time. Then an
innovative course-to-fine approach to detect the key points on the hand
is described. A new algorithm is used to find the candidate key points
coarsely and quickly. In finely stage, we verify the hand key points
with the shape context descriptor. To make the user much comfortable,
it can process the hand image with different poses, even the hand is
closed. Experiments show promising result by using the proposed
method in various conditions.
Abstract: Due to some reasons, observed images are degraded which are mainly caused by noise. Recently image denoising using the wavelet transform has been attracting much attention. Waveletbased approach provides a particularly useful method for image denoising when the preservation of edges in the scene is of importance because the local adaptivity is based explicitly on the values of the wavelet detail coefficients. In this paper, we propose several methods of noise removal from degraded images with Gaussian noise by using adaptive wavelet threshold (Bayes Shrink, Modified Bayes Shrink and Normal Shrink). The proposed thresholds are simple and adaptive to each subband because the parameters required for estimating the threshold depend on subband data. Experimental results show that the proposed thresholds remove noise significantly and preserve the edges in the scene.