L. Pratap Reddy

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The lm resolution IKONOS data has been used for the experiment.

A triband swastika shaped patch antenna with reduced mutual coupling for wireless mimo systems

A novel compact Swastika shaped patch antenna is designed in the present work, which can be used for Multiple Input Multiple Output (MIMO) systems. The proposed two element MIMO system resonates at a triband of 3.3 GHz, 5.8 GHz, and 7.1 GHz with an improved impedance bandwidth of 37% and a reduced mutual coupling of −33 dB. These results are better compared to a normal E shaped patch antenna designed with same size and thickness, achieved without using any additional decoupling methods. A 2×2 MIMO system employing the Swastika shaped patch antennas is analyzed using computational electromagnetic ray tracing software for an indoor environment. The results show an improvement in the capacity compared to a 2×2 MIMO system developed with dipole antennas. The proposed antenna is a good choice for MIMO systems operating for several Ultra WideBand (UWB) applications.

Image quality assessment based on perceptual structural similarity

We present a full reference objective image quality assessment technique which is based on the properties of the human visual system (HVS). It consists of two major components: 1) structural similarity measurement (SSIM) between the reference and distorted images, mimicking the overall functionality of HVS in a top down frame work. 2) A visual attention model which indicates perceptually important regions in the reference image based on the characteristics of intermediate and higher visual processes through the use of Importance Maps. Structural similarity in a region is weighted, depending on the perceptual importance of the region to arrive at Perceptual Structural Similarity Metric (PSSIM) indicative of the image quality.

Adaptive Binarization of Ancient Documents

It is common for libraries to provide public access to historical and ancient document image collections. Such document images to require specialized processing in order to remove background noise and become more legible. In this paper the proposed approach is adapted from the kavallieratov’s algorithm for cleaning background noise from the ancient documents by iterative global thresholding and local thresholding technique. Finally the image quality is enhanced by using morphological technique and compared with other methods in the process of cleaning.

Touching Syllable Segmentation using Split Profile Algorithm

The most challenging task of a character recognition system is associated with segmentation of individual components of the script with maximum efficiency. This process is relatively easy with regard to stroke based and standard scripts. Cursive scripts are more complex possessing a large number of overlapping and touching objects, where in the statistical behavior of the topological properties are to be studied extensively for achieving highest accuracy. Certain amount of similarity exists between unconstrained hand written text as well as South Indian scripts in terms of topology, component combinations, overlapping and merging characteristics. The concept of syllables and their formulations is an additive complexity with regard to Indian scripts. In this paper the statistical behavior of the cursive script, Telugu, is presented. The topological properties in terms of zones, component combinations, behavioural aspects of syllables are studied and adopted in the segmentation process. The statistical behaviour of cursive components are evaluated. Split Profile Algorithm is proposed while handling touching components. The proposed algorithm is evaluated on different fonts and sizes. The performance of the proposed algorithm is compared with two approaches methods viz aspect ratio and syllable width approaches.

Contrast Weighted Perceptual Structural Similarity Index for Image Quality Assessment

In this paper a full reference objective image quality assessment technique is presented which is based on the properties of the human visual system (HVS). By integrating the notion of perceptually important regions with the measurement of structural similarity between the original image and distorted image a contrast weighted Perceptual Structural SIMilarity Index PSSIM c is proposed. The method first evaluates the structural similarity indices between the original and distorted image in local regions. These local indices are then weighted based on the perceptual weights of the corresponding region, characterized by the contrast value of the local region. PSSIM c of an image is calculated as the average of these weighted indices. A comparison with the peak-signal-to-noise ratio (PSNR) and state of the art metric, Mean Structural Similarity Index (MSSIM), shows that the proposed measure correlates better with the judgment of human observers.

Segmentation of Touching Hand Written Numerals and Alphabets

Segmentation of touching hand written numerals and alphabets is a difficult task for recognizing individual characters. In this paper, the proposed algorithm is adopted from condego for the segmentation of hand written touching numerals, and is extended to segment the touching hand written English alphabets. The proposed method using Drop-fall algorithm is based on the moving of a marble on either side of the touching characters for selection of the point from where the cutting of the fused components should take place. This method improvers the segmentation accuracy.

Canonical syllable segmentation of Telugu document images

We propose a classical approach in the segmentation of canonical syllables of Telugu document images. Connected component approach is a simple strategy adopted until recent period. In this paper we propose a canonical syllable model which is equivalent to canonical structure C(C(CV))). The model consists of zone separation and component extraction phases as independent parts. The relation between zones and components is established in the segmentation process of canonical syllable. The segmentation efficiency of the proposed model is evaluated with respect to the canonical groups.

Local mesh quantized extrema patterns for image retrieval

In this paper, we propose a new feature descriptor, named local mesh quantized extrema patterns (LMeQEP) for image indexing and retrieval. The standard local quantized patterns collect the spatial relationship in the form of larger or deeper texture pattern based on the relative variations in the gray values of center pixel and its neighbors. Directional local extrema patterns explore the directional information in 0°, 90°, 45° and 135° for a pixel positioned at the center. A mesh structure is created from a quantized extrema to derive significant textural information. Initially, the directional quantized data from the mesh structure is extracted to form LMeQEP of given image. Then, RGB color histogram is built and integrated with the LMeQEP to enhance the performance of the system. In order to test the impact of proposed method, experimentation is done with bench mark image repositories such as MIT VisTex and Corel-1k. Avg. retrieval rate and avg. retrieval precision are considered as the evaluation metrics to record the performance level. The results from experiments show a considerable improvement when compared to other recent techniques in the image retrieval.

Binarization of Documents with Complex Backgrounds

In this paper, a novel heuristic based approach adopted from George D.C. Calvacanti algorithm for removing background noise from all types of images with complex background is presented. In this approach Binarization is done by selecting two threshold values, one for foreground and another for background for the separation. Morphological techniques are used for improving the quality of the resultant image. In addition to this PSNR ratio is calculated for all the images and its variation with respect to the intensity of the background noise is observed.