Current Issue : January - March Volume : 2012 Issue Number : 1 Articles : 5 Articles
An artificial cell is comprised of the most basic elements in a hierarchical system, that has minimal functionality, but general enough to obey the rules of ââ?¬Å?artificial life.ââ?¬Â The ability to replicate, organize hierarchy, and generalize within an environment is some of the properties of an artificial cell. We present a hardware artificial cell having the properties of generalization ability, the ability of self-organization, and the reproducibility. The cells are used in parallel hardware architecture for implementing the real-time 2D image convolution operation. The proposed hardware design is implemented on FPGA and tested on images. We report improved processing speeds and demonstrate its usefulness in an image filtering application....
The important task of library book inventory, or shelf-reading, requires humans to remove each book from a library shelf, open the front cover, scan a barcode, and reshelve the book. It is a labor-intensive and often error-prone process. Technologies such as 2D barcode scanning or radio frequency identification (RFID) tags have recently been proposed to improve this process. They both incur significant upfront costs and require a large investment of time to fit books with special tags before the system can be productive. A vision-based automation system is proposed to improve this process without those prohibitively high upfront costs. This low-cost shelf-reading system uses a hand-held imaging device such as a smartphone to capture book spine images and a server that processes feature descriptors in these images for book identification. Existing color feature descriptors for feature matching typically use grayscale feature detectors, which omit important color edges. Also, photometric-invariant color feature descriptors require unnecessary computations to provide color descriptor information. This paper presents the development of a simple color enhancement feature descriptor called Color Difference-of-Gaussians SIFT (CDSIFT). CDSIFT is well suited for library inventory process automation, and this paper introduces such a system for this unique application....
The appearance of human faces can undergo large variations over aging progress. Analysis of facial image taken over age progression recently attracts increasing attentions in computer-vision community. Human abilities for such analysis are, however, less studied. In this paper, we conduct a thorough study of human ability on two tasks, face verification and age estimation, for facial images taken at different ages. Detailed and rigorous experimental analysis is provided, which helps understanding roles of different factors including age group, age gap, race, and gender. In addition, our study also leads to an interesting observation: for age estimation, photos from adults are more challenging than that from young people. We expect the study to provide a reference for machine-based solutions....
Handwritten digit recognition is an important benchmark task in computer vision. Learning algorithms and feature representations which offer excellent performance for this task have been known for some time. Here, we focus on two major practical considerations: the relationship between the the amount of training data and error rate (corresponding to the effort to collect training data to build a model with a given maximum error rate) and the transferability of models' expertise between different datasets (corresponding to the usefulness for general handwritten digit recognition). While the relationship between amount of training data and error rate is very stable and to some extent independent of the specific dataset usedââ?¬â?only the classifier and feature representation have significant effectââ?¬â?it has proven to be impossible to transfer low error rates on one or two pooled datasets to similarly low error rates on another dataset. We have called this weakness brittleness, inspired by an old Artificial Intelligence term that means the same thing. This weakness may be a general weakness of trained image classification systems....
The main goal of medical imaging applications is to diagnose some diseases, try to prevent the progression of them, and actually cure the patients. The number of people that suffer from diabetes is growing very fast these recent years in many countries and it is needed to diagnose this disease in the beginning to prevent the subsequent side effects like blindness and so on. One of the first ways to detect this disease is analysis of vessels in some parts of the eye such as retina and conjunctiva. Some studies have been done on effects of vessel changes of conjunctiva in diabetes diagnosis and it is proved that conjunctival vessel extraction and analysis is a good way for this purpose. In this paper, we proposed a method to detect and extract the vessels of conjunctiva automatically. It is the first stage of the process of diabetes diagnosis. We first extract some textural features from each pixel of the conjunctiva image using LBP and then classify each pixel to vessels or nonvessels according to the features vector based on a supervised classifier, ANFIS. We tested the proposed algorithm on 40 conjunctival images to show the performance and efficiency of our method....
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