Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

Development Planning at the State Level in India - A Case Study with Reference to Kerala, 1957-'84

This thesis entitled “Development planning at the state level in india a case study with reference to kerala1957-84.Planning in India is a concurrent subject with the Centre and the States having well-defined domains of jurisdiction with regard to planning functions and sources of resource mobilisation.The genesis of the lack of academic interest in state level planning is in the widely held belief that in the extent scheme of Centre-State economic relations, the states have little scope for initiative in planning.Both at the theoretical and empirical levels, Kerala has attached very great importance to planning.It has been the localeof wide and deep discussions on the various dimensions of planning.In Kerala's development process, the leading sector consists of social services such as education and public healthOne point that needs special emphasis in this regard is that the high demand for education in Kerala cannot be attributed to the Keralites' ‘unique urge‘ for education. Rather, it is related to the very high level of unemployment in the state (Kerala has the highest level of unemployment in the country.In resource allocation under the Five Year Plans, Kerala attached the highest weightage to power generation, hydro-electric projects being the major source of power in the state. Nearly one-fourth of the plan resources has been claimed by hydro-electric projects.In the agricultural sector, Kera1a's level of productive use of electric power is one of the lowest.As is evident.from above, planning in Kerala has not enabled us to solve the basic problems of the state. More 'scientific' planning in the sense of applying mre sophisticated planning techniques is obviously not the answer. It, on the contrary, consists of more fundamental changes some of which can be brought about through an effective use of measures well within the power of the State Government.

A Writer Identification System For Handwritten Malayalam Documents

Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters

Automatic Image Annotation Using SURF Descriptors

In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics.