A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Antibiotic resistance pattern of motile aeromonads from farm raised fresh water fish

Motile aeromonads isolated from the intestines of farm-raised freshwater fish such as Catla catla, Labeo rohita and Ctenopharyngodon idella have been characterized to species level. Morphological and physiological grouping revealed 61% Aeromonas hydrophila, 30% Aeromonas caviae, 7% Aeromonas sobria and 2% which remained unidentified. Hemolytic activity was detected mostly in A. hydrophila, while only half of the A. sobria and A. caviae showed this activity. Antibiotic resistance patterns of the strains revealed that they had acquired a relatively higher resistance to oxytetracycline, amoxycillin, ampicillin, novobiocin and polymixin-B, implicating possible use of these antibiotics in the aquaculture systems.

Virulence Potential And Antibiotic Susceptibility Pattern Of Motile Aeromonads Associated With Freshwater Ornamental Fish Culture Systems: A Possible Threat To public Health

Aeromonas spp. are ubiquitous aquatic organisms, associated with multitude of diseases in several species of animals, including fishes and humans. In the present study, water samples from two ornamental fish culture systems were analyzed for the presence of Aeromonas. Nutrient agar was used for Aeromonas isolation, and colonies (60 No) were identified through biochemical characterization. Seven clusters could be generated based on phenotypic characters, analyzed by the programme NTSYSpc, Version 2.02i, and identified as: Aeromonas caviae (33.3%), A. jandaei (38.3%) and A. veronii biovar sobria (28.3%). The strains isolated produced highly active hydrolytic enzymes, haemolytic activity and slime formation in varying proportions. The isolates were also tested for the enterotoxin genes (act, alt and ast), haemolytic toxins (hlyA and aerA), involved in type 3 secretion system (TTSS: ascV, aexT, aopP, aopO, ascF–ascG, and aopH), and glycerophospholipid-cholesterol acyltransferase (gcat). All isolates were found to be associated with at least one virulent gene. Moreover, they were resistant to frequently used antibiotics for human infections. The study demonstrates the pathogenic potential of Aeromonas, associated with ornamental fish culture systems suggesting the emerging threat to public health

Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images

Pattern Analysis Techniques for the Recognition of Unconstrained Handwritten Malayalam Character Images

The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate

Temporal pattern of fish production in a microtidal tropical estuary in the south-west coast of India

The status of fisheries and seasonal variation in fish diversity in the Kodungallur-Azhikode Estuary (KAE) were investigated. Total annual average fish production in the estuary declined significantly to 908.6 t with average yield of 5.4 kg ha-1 day-1, when compared to earlier study; where 2747 t was reported. During the present study, 60 species of finfishes (belonging to 34 finfish families), 6 species of penaeid shrimps, 2 species of palaemonid prawns, 2 species of crabs (4 crustacean families), 6 species of bivalves and 2 species of edible oysters (3 molluscan families) were noticed. Finfishes were the major group that contributed 69.62% of total fishery in the estuary and crustaceans (23.47%), bivalves (6.84%) and oysters (0.07%) also formed good fishery. Many of the fish species in the estuary were observed as threatened (Horabagrus brachysoma, Channa striatus, Channa marulius, Clarias batrachus, Heteropneustes fossilis and Wallago attu). The major fishing gears employed in the estuary were gillnets, cast nets, stake nets, scoop nets, ring nets, traps and Chinese dip nets. Gillnets contributed 45% of the total fish catch. Gillnets also showed highest catch per unit effort (CPUE) of 6.91 kg h -1 followed by cast nets (1.85 kg h -1), Chinese dip nets (3.20 kg h -1), stake nets (3.05 kg h -1), ring nets (1.27 kg h -1), hooks and lines (1.35 kg h -1) and scoop nets (0.92 kg h -1). The study implies that temporal changes in fish landing pattern of the KAE was mainly due to environmental variability, habitat modification and fish migration; under the influence of south-west monsoon and anthropogenic activities in the KAE. Results of the study suggest that spatio-temporal variations in the fish community structure could be an indicator for anthropogenic stress and it should be considered for restoration programmes.

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.

Statistical evaluation of texture analysis from the biocrystallization method

The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

Improving food and nutritional security of small and marginal coconut growers through diversification of crops and enterprises

This paper presents the impact of integrating interventions like nutrition gardening, livestock rearing, product diversification and allied income generation activities in small and marginal coconut homesteads along with nutrition education in improving the food and nutritional security as well as the income of the family members. The activities were carried out through registered Community Based Organizations (CBOs) in three locations in Kerala, India during 2005-2008. Data was collected before and after the project periods through interviews using a pre-tested questionnaire containing statements indicating the adequacy, quality and diversity of food materials. Fifty respondents each were randomly selected from the three communities, thereby resulting in a total sample size of 150. The data was analysed using SPSS by adopting statistical tools like frequency, average, percentage analysis, t – test and regression. Participatory planning and implementation of diverse interventions notably intercropping and off-farm activities along with nutrition education brought out significant improvements in the food and nutritional security, in terms of frequency and quantity of consumption as well as diet diversity. At the end of the project, 96%of the members became completely food secure and 72% nutritionally secure. The overall consumption of fruits, vegetables and milk by both children and adults and egg by children recorded increase over the project period. Consumption of fish was more than the Recommended Dietary Intake (RDI) level during pre and post project periods. Project interventions like nutrition gardening could bring in surplus consumption of vegetables (35%) and fruits (10%) than RDI. In spite of the increased consumption of green leafy vegetables and milk and milk products over the project period, the levels of consumption were still below the RDI levels. CBO-wise analysis of the consumption patterns revealed the need for location-specific interventions matching to the needs and preferences of the communities.

Resource use pattern and agroecosystem functioning in Rawanganga micro-watershed in Garhwal Himalaya, India

Agro-ecological resource use pattern in a traditional hill agricultural watershed in Garhwal Himalaya was analysed along an altitudinal transect. Thirty one food crops were found, although only 0.5% agriculture land is under irrigation in the area. Fifteen different tree species within agroforestry systems were located and their density varied from 30-90 trees/ha. Grain yield, fodder from agroforest trees and crop residue were observed to be highest between 1200 and 1600 m a.s.l. Also the annual energy input- output ratio per hectare was highest between 1200 and 1600 m a.s.l. (1.46). This higher input- output ratio between 1200-1600 m a.s.l. was attributed to the fact that green fodder, obtained from agroforestry trees, was considered as farm produce. The energy budget across altitudinal zones revealed 95% contribution of the farmyard manure and the maximum output was in terms of either crop residue (35%) or fodder (55%) from the agroforestry component. Presently on average 23%, 29% and 41% cattle were dependent on stall feeding in villages located at higher, lower and middle altitudes respectively. Similarly, fuel wood consumption was greatly influenced by altitude and family size. The efficiency and sustainability of the hill agroecosystem can be restored by strengthening of the agroforestry component. The approach will be appreciated by the local communities and will readily find their acceptance and can ensure their effective participation in the programme.

Finding Spaces for Urban Food Production – Matching Spatial and Stakeholder Analysis with Urban Agriculture Approaches in the Urban Renewal Area of Dortmund-Hörde, Germany

Using the case of an economically declined neighbourhood in the post-industrial German Ruhr Area (sometimes characterized as Germany’s “Rust Belt”), we analyse, describe and conclude how urban agriculture can be used as a catalyst to stimulate and support urban renewal and regeneration, especially from a socio-cultural perspective. Using the methodological framework of participatory action research, and linking bottom-up and top-down planning approaches, a project path was developed to include the population affected and foster individual responsibility for their district, as well as to strengthen inhabitants and stakeholder groups in a permanent collective stewardship for the individual forms of urban agriculture developed and implemented. On a more abstract level, the research carried out can be characterized as a form of action research with an intended transgression of the boundaries between research, planning, design, and implementation. We conclude that by synchronously combining those four domains with intense feedback loops, synergies for the academic knowledge on the potential performance of urban agriculture in terms of sustainable development, as well as the benefits for the case-study area and the interests of individual urban gardeners can be achieved.

Model-Based Matching by Linear Combinations of Prototypes

We describe a method for modeling object classes (such as faces) using 2D example images and an algorithm for matching a model to a novel image. The object class models are "learned'' from example images that we call prototypes. In addition to the images, the pixelwise correspondences between a reference prototype and each of the other prototypes must also be provided. Thus a model consists of a linear combination of prototypical shapes and textures. A stochastic gradient descent algorithm is used to match a model to a novel image by minimizing the error between the model and the novel image. Example models are shown as well as example matches to novel images. The robustness of the matching algorithm is also evaluated. The technique can be used for a number of applications including the computation of correspondence between novel images of a certain known class, object recognition, image synthesis and image compression.