Classical swine fever is a highly contagious viral disease of swine causing economic losses due to heavy mortality and reproductive problems. The present study was conducted at Nakalapuram village, Villathikulam taluk of Thoothukudi District, Tamilnadu where there was a suspected outbreak of swine fever among the indigenous pigs reared under scavenging system. Ninety pigs out of one hundred and ten pigs of all age groups without any vaccination died within two to three days period. The ailing animals showed clinical signs such as high fever, staggering gait, frothy excessive salivation, severe respiratory distress, paddling of legs with convulsions followed by death. The post mortem examination was carried out in two pigs and the histopathological examination was carried out on representative necropsy samples like liver, spleen, kidney and mesenteric lymph node. Based on the necropsy findings such as haemorrhagic lymphadenitis, petechial haemorrhages in kidney and spleen and by NS5B gene based RT-PCR the disease was confirmed as classical swine fever.
For an efficient image security, image hashing is one of the solutions for image authentication. A robust image hashing mechanism must be robust to image processing operations as well as geometric distortions. A better hashing technique must ensure an efficient detection of image forgery like insertion, deletion, replacement of objects, malicious color tampering, and for locating the exact forged areas. This paper describes a novel image hash function, which is generated by using both global and local features of an image. The global features are the representation of Zernike moments on behalf of luminance and chrominance components of the image as a whole. The local features include texture information as well as position of significant regions of the image. The secret keys can be introduced into the system, in places like feature extraction and hash formulation to encrypt the hash. The hash incorporation into the system is found very sensitive to abnormal image modifications and hence robust to splicing and copy-move type of image tampering and, therefore, can be applicable to image authentication. As in the generic system, the hashes of the reference and test images are compared by finding the hamming or hash distance. By setting the thresholds with the distance, the received image can be stated as authentic or non-authentic. And finally location of forged regions and type of forgery are found by decomposing the hashes. Compared to most recent work done in this area, our algorithm is simple and cost effective with better scope of security.
The concept of the global information infrastructure and specifically that of the World Wide Web (WWW) has led to users accessing data of different media including images and video data over a wide area network. These data objects have sizes the order of megabytes and communication time is very large. The data size can he reduced without losing information by applying loss-inducing techniques and this will lead to reduction in communication time. Several loss-inducing techniques have heen developed and each image is treated differently by each technique. In some cases an acceptable quality of the image is obtained and in some cases it is not. In this paper we develop a color-based technique to quantify the data loss when a loss-inducing technique i.s applied to an image. This will result in estimating whether the resulting image is indistinguishable from the original with respect to the human eye. We illustrate its use to classify images according to the loss they can tolerate. This avoids redundant communication of a high quality image when a lower quality image can satisfy the application resulting in the conservation and better usage of network resources. We present the technique, the communication time saved, and an experimental evaluation to prove the validity of the technique.
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