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In this paper we propose a neural net based characters recognition scheme for Bangla printed text books. There are a lot of scientific literature, novels, magazines and books etc that are written in Bangla language. More than 400 million people use Bangla language. Most of the library and educational institutions want to keep copy of the books in a digital format. For storing those books in digital...
License plate detection and character recognition have unveiled new possibilities and challenges in the field of intelligent transport system. Numerous algorithms have been proposed regarding license plate localization and tracking, character segmentation and character recognition. License plate character recognition is still an active area of research specially in terms of processing complexity....
Cytogenetic is a branch of genetics that is concerned with the study of the structure and function of the cell, especially the chromosomes. The chromosomal identification is of prime importance to geneticist for diagnosing various abnormalities. The existing system is developed to classify the chromosomes based on pixel distribution, centromere index and band patterns using artificial neural network...
This paper presents a novel approach for the generation of 3D building model from IKONOS satellite image data. The main idea of 3D modeling is based on the grouping of 3D line segments. The divergence-based centroid neural network is employed in the grouping process. Prior to the grouping process, 3D line segments are extracted with the aid of the elevation information obtained by using area-based...
Texture classification is an important and challenging factor in image processing system which refers to the process of partitioning a digital image into multiple constituent segments. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Artificial Neural Network (ANN) Based texture classification or Segmentation...
High-throughput microscopy allows fast imaging of large tissue samples, producing an unprecedented amount of sub-cellular information. The size and complexity of these data sets often out-scale current reconstruction algorithms. Overcoming this computational bottleneck requires extensive parallel processing and scalable algorithms. As high-throughput imaging techniques move into main stream research,...
A Research of maize disease image recognition of corn leaf based on image processing and analysis, which is to study diseases of image classification. According to the texture characteristics of corn diseases, it uses YCbCr color space technology to segment disease spot, and uses the cooccurrence matrix spatial gray level layer to extract disease spot texture feature, and uses BP neural network to...
The following topics are dealt with: exponential change-points model; Fourier transform; forecasting sunspot numbers; distributed temperature measurements; software development; adaptive observer based tracking control; FPGA bases analysis; maximum power point tracking based optimal control; visual indicator component software; dye-sensitized solar cell; feedback delay effect; thresholding algorithm;...
The principal goal of the segmentation process is to partition an image into classes or subsets that are homogeneous with respect to one or more characteristics or features. In medical imaging, segmentation is important for feature extraction, image measurements, and image display. This study presents a new version of complex-valued artificial neural networks (CVANN) for the biomedical image segmentation...
One of the most considerations in the field of chromosome analysis is the segmentation and determination of the centromere detection and karyotying of the chromosomes. Previously depend upon centromere position and its angle with the p-arm and q-arm positions, bond comparisons as made the classification of chromosomes and the pairing possibilities of the chromosomes. Such that in this paper as describe...
We propose and evaluate a framework for detection of plant leaf/stem diseases. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively expensive, especially in developing countries. Providing fast, automatic, cheap and accurate image-processing-based solutions for that task can be of great realistic significance. The proposed framework is image-processing-based...
The objective of the present study is to develop an automatic tool to identify and classify the different types of cocci bacterial cells in digital microscopic cell images using active contour method. Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Geometric features are used to identify the arrangement...
Image thresholding is a very important phase in the image analysis process. However, different images have different characteristics making the traditional process of thresholding by one algorithm a very challenging task. That is because any thresholding method may be perform well for some images but for sure it will not be suitable for all images. In this paper, intelligent thresholding by training...
In this paper, a computer-based method for defining tumor region in the brain using MRI images is presented. A classification of brain into healthy brain or a brain having a tumor is first done which is then followed by further classification into begnin or malignant tumor. The algorithm incorporates steps for preprocessing, image segmentation, feature extraction and image classification using neural...
This paper describes a method using image processing and genetic algorithm-neural network (GA-NN) for automated Mycobacterium tuberculosis detection in tissues. The proposed method can be used to assist pathologists in tuberculosis (TB) diagnosis from tissue sections and replace the conventional manual screening process, which is time-consuming and labour-intensive. The approach consists of image...
A satellite precipitation estimation algorithm based on wavelet features is investigated to find the optimal wavelet features in terms of wavelet family and sliding window size. In this work, the infrared satellite based images along with ground gauge (radar corrected) observations are used for the retrieval rainfall. The goal of this work is to find an optimal wavelet transform to represent better...
The following topics are dealt with: linear approximation; license plate recognition; color image segmentation; image quantization; wireless video transmission; congestion control; stochastic search; transmembrane helical segments; wavelet transform; semisupervised cluster algorithm; anomaly detection; data privacy; online market information processing; user behavior; particle swarm optimization;...
A pulmonary nodule is the most common sign of lung cancer. The proposed system efficiently predicts lung tumor from Computed Tomography (CT) images through image processing techniques coupled with neural network classification as either benign or malignant. The lung CT image is denoised using non-linear total variation algorithm to remove random noise prevalent in CT images. Optimal thresholding is...
With the research and development of chess robot and machine vision, chess robot with visual function has recently received an increasing interest in the community. This paper introduces the chess system of dual-robot coordination based on vision and the process of visual system structure, gives the coordinates translation from computer and image coordinates to actual coordinates. And in the process...
Skin color detection is an important subject in computer vision research. Color segmentation takes a great attention because color is an effective and robust visual cue for characterizing an object from the others. To aim at existing skin color algorithms considering the luminance information not enough, a reliable color modeling approach was proposed. It is based on the fact that color distribution...
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