DIA in Agriculture

Automated Rice Leaf Disease Detection Using Color Image Analysis

By R.A.D.L. Pugoy and V.Y. Mariano, in  3rd International Conference on Digital Image Processing (ICDIP 2011), Chengdu, China, 15-17 April 2011

Abstract
In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as manual eyeball exercise, is important to come up with good nutrient and disease management strategies.
In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.

Mariano Details
Vladimir Y. Mariano,

Associate Professor, Institute of Computer Science,

The University of the Philippines Los Baños.

 

Source:: http://www.ics.uplb.edu.ph/node/477

Modelling indoors

Three-dimensional models of objects, sites, buildings, structures, and urban environments made of geometry and texture are important in a variety of civilian and military applications such as training and simulation for disaster management, counteracting terrorism, virtual heritage conservation, virtual museums, historical sites documentation, mapping of hazardous sites and underground tunnels, and modeling of industrial and power plants for design verification and manipulation.
While object modeling has received a great deal of attention in recent years, 3D site modeling, particularly for indoor environments, poses significant challenges. The main objective of this proposal is to design, analyze, and develop architecture and algorithms, as well as associated statistical and mathematical framework for a human operated, portable, 3D indoor/outdoor modeling system, capable of generating photo-realistic rendering of the internal structure of multi-story buildings as well as external structure of a collection of buildings in a campus.


BEWARE
FOLLOWING LINK CONTAINS HUGE SIZE PHOTOS. SO IT EATS LOT OF BANDWIDTH

Source:: http://www-video.eecs.berkeley.edu/research/indoor/

Gang Graffiti Recognition

Gang Graffiti Recognition and Analysis Using a Mobile Telephone

Gangs are a serious threat to public safety throughout the United States. Gang members are continuously migrating from urban cities to suburban areas. They are responsible for an increasing percentage of crime and violence in many communities.

According to the National Gang Threat Assessment, approximately 1 million gang members belonging to more than 20,000 gangs were criminally active within all 50 states and the District of Columbia as of September 2008. Criminal gangs commit as much as 80 percent of the crime in many communities according to law enforcement officials throughout the nation.

Street gang graffiti is their most common way to communicate messages, including challenges, warnings or intimidation to rival gangs. It is, however, an excellent way to track gang affiliation and growth, or even sometimes to obtain membership information.

The goal of this project is to use the knowledge gained from our work in mobile devices and applications and leverage it towards the development of a mobile-based system capable of image analysis. This system will provide an accurate and useful output to a user based on a database of gang graffiti images.

The image analysis includes obtaining the metadata (geoposition, date and time) and extracting relevant features (e.g., color, shape) from the gang graffiti image. The information is sent to a server and compared against the graffiti image database. The matched results are sent back to the device where the user can then review the results and provide extra inputs to refine information. Once the graffiti is completely decoded and interpreted, it is labeled and added to the database.


https://redpill.ecn.purdue.edu//~gari/web/index.html

Printer Identification

    Techniques are available  to secure documents such as bank notes using paper watermarks, security fibers, holograms, or special inks. The problem is that the use of these security techniques can be cost prohibitive. Most of these techniques either require special equipment to embed the security features, or are simply too expensive for an average consumer. Additionally, there are a number of applications in which it is desirable to be able to identify the technology, manufacturer, model, or even specific unit that was used to print
a given document.
 
    The print quality defect known as banding in electrophotographic (EP ie LASER) printers helps  to identify the model and manufacturer of the printer. Generally different printers have different sets of banding frequencies which are dependent upon brand and model. Using this banding frequencies printers are identified. In forensics if they are able to find the printer details then from that they can trace the dealer and retailer. This in will lead them to find the criminal they are lookin for.

Paper Title :: High-Capacity Data Hiding in Text Documents,
Authors:: Aravind K. Mikkilineni,George T. C. Chiu , Jan P. Allebach , Edward J. Delp


Source :: Purdue Sensor and Printer Forensics (PSAPF)

The goals of their work are to securely print and trace documents on low cost consumer printers such as inkjet and electrophotographic (laser) printers.

http://cobweb.ecn.purdue.edu/~prints/