Abstract: Bagh-e Dasht area is situated in the northern part of Herat, an old city in western Afghanistan located on the Silk Road which has received a strong influence from Persian culture. Initially, the Bagh-e Dasht area was developed for gardens and palaces near Joy-e Injil canal during the Timurid Empire in the 15th century. It is assumed Bagh-e Dasht became a settlement in the 16th century during the Safavid Empire. The oldest area is the southern part around the canal bank which is characterized by Dalans, sun-dried brick arcades above which houses are often constructed. Traditional houses in this area are built with domical vault roofs constructed with sun-dried bricks. Bagh-e Dasht is one of the best-preserved settlements of traditional houses in Herat. This study examines the transformation of the Bagh-e Dasht area with a focus on Dalans, where traditional houses with domical vault roofs have been well-preserved until today. The aim of the study is to examine the extent of physical changes to the area as well as changes to houses and the community. This research paper contains original results which have previously not been published in architectural history. The roof types of houses in the area are investigated through examining high resolution satellite images. The boundary of each building and space is determined by both a field survey and aerial photographs of the study area. A comprehensive field survey was then conducted to examine each space and building in the area. In addition, a questionnaire was distributed to the residents of the Dalan houses and interviews were conducted with the Wakil (Chief) of the area, a local historian, residents and traditional builders. The study finds that the oldest part of Bagh-e Dasht area, the south, contains both Dalans and domical vault roof houses. The next oldest part, which is the north, only has domical vault roof houses. The rest of the area only has houses with modernized flat roofs. This observation provides an insight into the process of historical development in the Bagh-e Dasht area.
Abstract: Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.
Abstract: Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.
Abstract: This paper presents an overview of the methodologies
and algorithms for statistical texture analysis of 2D images. Methods
for digital-image texture analysis are reviewed based on available
literature and research work either carried out or supervised by the
authors.
Abstract: Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.
Abstract: This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.
Abstract: In the course of recent decades, medical imaging has
been dominated by the use of costly film media for review and
archival of medical investigation, however due to developments in
networks technologies and common acceptance of a standard digital
imaging and communication in medicine (DICOM) another approach
in light of World Wide Web was produced. Web technologies
successfully used in telemedicine applications, the combination of
web technologies together with DICOM used to design a web-based
and open source DICOM viewer. The Web server allowance to
inquiry and recovery of images and the images viewed/manipulated
inside a Web browser without need for any preinstalling software.
The dynamic site page for medical images visualization and
processing created by using JavaScript and HTML5 advancements.
The XAMPP ‘apache server’ is used to create a local web server for
testing and deployment of the dynamic site. The web-based viewer
connected to multiples devices through local area network (LAN) to
distribute the images inside healthcare facilities. The system offers a
few focal points over ordinary picture archiving and communication
systems (PACS): easy to introduce, maintain and independently
platforms that allow images to display and manipulated efficiently,
the system also user-friendly and easy to integrate with an existing
system that have already been making use of web technologies. The
wavelet-based image compression technique on which 2-D discrete
wavelet transform used to decompose the image then wavelet
coefficients are transmitted by entropy encoding after threshold to
decrease transmission time, stockpiling cost and capacity. The
performance of compression was estimated by using images quality
metrics such as mean square error ‘MSE’, peak signal to noise ratio
‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when
‘coif3’ wavelet filter is used.
Abstract: Eyes are considered to be the most sensitive and
important organ for human being. Thus, any eye disorder will affect
the patient in all aspects of life. Cataract is one of those eye disorders
that lead to blindness if not treated correctly and quickly. This paper
demonstrates a model for automatic detection, classification, and
grading of cataracts based on image processing techniques and
artificial intelligence. The proposed system is developed to ease the
cataract diagnosis process for both ophthalmologists and patients.
The wavelet transform combined with 2D Log Gabor Wavelet
transform was used as feature extraction techniques for a dataset of
120 eye images followed by a classification process that classified the
image set into three classes; normal, early, and advanced stage. A
comparison between the two used classifiers, the support vector
machine SVM and the artificial neural network ANN were done for
the same dataset of 120 eye images. It was concluded that SVM gave
better results than ANN. SVM success rate result was 96.8%
accuracy where ANN success rate result was 92.3% accuracy.
Abstract: Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.
Abstract: Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.
Abstract: The objective of this paper is to investigate the formation and adhesion of a protective aluminum-oxide (Al2O3, alumina) layer on the surface of Iron-Chromium-Aluminum Alloy (Fe-Cr-Al) sintered-metal-fibers. The oxide-scale layer was developed via multi-stage thermal oxidation at 930 oC for 1 hour, followed by 1 hour at 960 oC, and finally at 990 oC for 2 hours. Scanning Electron Microscope (SEM) images show that the multi-stage thermal oxidation resulted in the formation of predominantly Al2O3 platelets-like and whiskers. SEM images also reveal non-uniform oxide-scale growth on the surface of the fibers. Furthermore, peeling/spalling of the alumina protective layer occurred after minimum handling, which indicates weak adhesion forces between the protective layer and the base metal alloy. Energy Dispersive Spectroscopy (EDS) analysis of the heat-treated Fe-Cr-Al sintered-metal-fibers confirmed the high aluminum content on the surface of the protective layer, and the low aluminum content on the exposed base metal alloy surface. In conclusion, the failure of the oxide-scale protective layer exposes the base metal alloy to further oxidation, and the fragile non-uniform oxide-scale is not suitable as a support for catalysts.
Abstract: This paper has its objectives to reveal contents and personality suitable to women’s newspapers. The research methodology employed in this study is the questionnaire which is derived from a literature review related to newspapers, graphic elements method for print media design and 12 sample sizes of different daily newspapers. In order to acquire an in-depth understanding and comprehensible view of desirable for a women’s newspaper design, graphic elements that related to that personality as well as other preferable elements for a women’s newspaper, including seven editorial Many Thai newspapers were offer a women’s documentary and column space. With its feminine looks, most of them appeared with warm tones and friendly mood through their headlines, contents, illustrations and graphics. The study found that most desirable personalities for a women’s newspaper design in Thailand are: Modern, Chic and Natural. Each personality has significant graphic elements as follows: 1. Modern: significant elements of modern personality comprises of the composition with graduation pattern which creates attractiveness by using an anomalous alignment layout grid and outstanding structure to create focal points and dynamic movement. Dark to black color that has narrowed, limited hue coupled with bright color tones. The round shape of the Thai font style was suitable for this concept. Such Thai fonts have harmonious proportion and consistent stroke with the urban-polite look. 2. Chic: significant elements of chic personality comprises of the proper composition with distinctive scale, using rhythmic repetition and a contrast of scale to draw in reader attention. Vivid and bright color tones with extensive hues coupled with similar color tones and round shape of the Thai font style with a light stroke and consistent line. 3. Natural: significant elements of natural personality comprises of the proper composition using rhythmic repetition that creates a focal point through striking images and harmonious perspective. Warm color tones with restricted hues that appear to look natural. Duo tone color was suitable through the gradually increasing gradient. The Thai style with hand writing font was suitable through the inconsistent stroke. There are 10 types of daily content that were revealed to be the most desirable for Thai women readers, these are: Daily News, Economics News, Education News, Entertainment News, International news, Political News, Public Health News, Scientific News, Social News and Sports News. As well, there are 16 topics identified as very desirable for Thai women readers, such as: Art and Culture, Automobile, Classified, Special Scoop, Editorial, Advertisement, Entertainment, Health and Quality of Life, History, Horoscope, Lifestyle and Fashion, Literature, Nature - Environment and Tourism, Night Life, Stars and Jet Set Gossip, Women’s Issue.
Abstract: This study assesses the major ecological zones in Nigeria with the view to understanding the spatial pattern of vegetation zones and the implications on conservation within the period of sixteen (16) years. Satellite images used for this study were acquired from the SPOT-VEGETATION between 1998 and 2013. The annual NDVI images selected for this study were derived from SPOT-4 sensor and were acquired within the same season (November) in order to reduce differences in spectral reflectance due to seasonal variations. The images were sliced into five classes based on literatures and knowledge of the area (i.e. 0.47 Forest Zone). Classification of the 1998 and 2013 images into forested and non forested areas showed that forested area decrease from 511,691 km2 in 1998 to 478,360 km2 in 2013. Differencing change detection method was performed on 1998 and 2013 NDVI images to identify areas of ecological concern. The result shows that areas undergoing vegetation degradation covers an area of 73,062 km2 while areas witnessing some form restoration cover an area of 86,315 km2. The result also shows that there is a weak correlation between rainfall and the vegetation zones. The non-vegetated areas have a correlation coefficient (r) of 0.0088, Sahel Savannah belt 0.1988, Sudan Savannah belt -0.3343, Guinea Savannah belt 0.0328 and Forest belt 0.2635. The low correlation can be associated with the encroachment of the Sudan Savannah belt into the forest belt of South-eastern part of the country as revealed by the image analysis. The degradation of the forest vegetation is therefore responsible for the serious erosion problems witnessed in the South-east. The study recommends constant monitoring of vegetation and strict enforcement of environmental laws in the country.
Abstract: Studies estimate that there will be 266,120 new cases
of invasive breast cancer and 40,920 breast cancer induced deaths
in the year of 2018 alone. Despite the pervasiveness of this
affliction, the current process to obtain an accurate breast cancer
prognosis is tedious and time consuming. It usually requires a
trained pathologist to manually examine histopathological images and
identify the features that characterize various cancer severity levels.
We propose MITOS-RCNN: a region based convolutional neural
network (RCNN) geared for small object detection to accurately
grade one of the three factors that characterize tumor belligerence
described by the Nottingham Grading System: mitotic count. Other
computational approaches to mitotic figure counting and detection
do not demonstrate ample recall or precision to be clinically viable.
Our models outperformed all previous participants in the ICPR 2012
challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14
challenge along with recently published works. Our model achieved
an F- measure score of 0.955, a 6.11% improvement in accuracy from
the most accurate of the previously proposed models.
Abstract: Digital multimedia contents such as image, video, and audio can be tampered easily due to the availability of powerful editing softwares. Multimedia forensics is devoted to analyze these contents by using various digital forensic techniques in order to validate their authenticity. Digital image forensics is dedicated to investigate the reliability of digital images by analyzing the integrity of data and by reconstructing the historical information of an image related to its acquisition phase. In this paper, a survey is carried out on the forgery detection by considering the most recent and promising digital image forensic techniques.
Abstract: Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.
Abstract: Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances.
Abstract: In this paper, we report the experimental results on using complementary Golay coded signals at 7.5 MHz to detect breast microcalcifications of 50 µm size. Simulations using complementary Golay coded signals show perfect consistence with the experimental results, confirming the improved signal to noise ratio for complementary Golay coded signals. For improving the success on detecting the microcalcifications, orthogonal complementary Golay sequences having cross-correlation for minimum interference are used as coded signals and compared to tone burst pulse of equal energy in terms of resolution under weak signal conditions. The measurements are conducted using an experimental ultrasound research scanner, Digital Phased Array System (DiPhAS) having 256 channels, a phased array transducer with 7.5 MHz center frequency and the results obtained through experiments are validated by Field-II simulation software. In addition, to investigate the superiority of coded signals in terms of resolution, multipurpose tissue equivalent phantom containing series of monofilament nylon targets, 240 µm in diameter, and cyst-like objects with attenuation of 0.5 dB/[MHz x cm] is used in the experiments. We obtained ultrasound images of monofilament nylon targets for the evaluation of resolution. Simulation and experimental results show that it is possible to differentiate closely positioned small targets with increased success by using coded excitation in very weak signal conditions.
Abstract: Ceramic, polymer and composite nanofibers are nowadays begun to be utilized in many fields of nanotechnology. By the means of dimensions, these fibers are as small as nano scale but because of having large surface area and microstructural characteristics, they provide unique mechanic, optical, magnetic, electronic and chemical properties. In terms of nanofiber production, electrospinning has been the most widely used technique in recent years. In this study, carbon nanofibers have been synthesized from solutions of Polyacrylonitrile (PAN)/ N,N-dimethylformamide (DMF) by electrospinning method. The carbon nanofibers have been stabilized by oxidation at 250 °C for 2 h in air and carbonized at 750 °C for 1 h in H2/N2. Images of carbon nanofibers have been taken with scanning electron microscopy (SEM). The images have been analyzed to study the fiber morphology and to determine the distribution of the fiber diameter using FibraQuant 1.3 software. Then polymer composites have been produced from mixture of carbon nanofibers and silicone polymer. The final polymer composites have been characterized by X-ray diffraction method and scanning electron microscopy (SEM) energy dispersive X-ray (EDX) measurements. These results have been reported and discussed. At result, homogeneous carbon nanofibers with 100-167 nm of diameter were obtained with optimized electrospinning conditions.
Abstract: Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.