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Gridding cDNA microarray images is a critical step in gene expression analysis, since any errors in this stage are propagated in future steps in the analysis. We propose a fully automatic approach to detect the locations of the spots. The approach first detects and corrects rotations in the sub-grids by an affine transformation, followed by a polynomial-time optimal multi-level thresholding algorithm...
For any autonomous system it is very important to acquire the knowledge of the surrounding environment. Images and videos acquired by the vision based sensors can provide meaningful information about the environment, which can be very useful for the navigation of autonomous system like mobile robots. To extract road information from image frames for navigation purpose they have to be classified. Classification...
Image fusion means merging two or more images in such a way as to preserving the most desirable characteristics of each image. Because of standard image fusion methods are often successful at adding spatial detail into the multispectral imagery but distort the colour information in the fusion process. So, the paper presents an approach for multi-resolution image fusion of a high-resolution SPOT (Satellite...
In this paper we present an almost automatic synthesis of a highly complex, throughput optimized architecture of an adaptive multiresolution filter as used in medical image processing for FPGAs. The filter consists of 16 parallel working modules, where the most computationally intensive module achieves software pipelining of a factor of 85, that is, computations of 85 iterations overlap each other...
This paper describes a pedestrian detection method using a LRF and a small omni-view camera. In outdoor environment, the resolutions of LRFs are too low to recognize human reliably, and high resolution image requires high calculation cost for detecting walking persons. We propose a combination approach using these data. Particle filter based tracking and HOG (Histogram of Oriented Gradients) feature...
A new digital image interpolation method that is performed in the wavelet domain with a least squares algorithm is presented in this paper. This method estimates wavelet coefficients in the high frequency sub-images of the estimated High-Resolution (HR) image from the Low-Resolution (LR) image using a least squares algorithm. An inverse wavelet transform is then performed for the synthesis of the...
Line detection in digital images is a fundamental aspect of many problems in computer vision. In the light of the problems, such as heavy computation and intensive memory occupation, existing in the Hough Transform, an improved fast line detection algorithm combining the time-frequency domain transform and the spatial domain transform is proposed. First, the wavelet lifting is used to extract low...
Autofocusing is an essential technique in many machine vision aided microscopy application. This paper presents a comparison study of 6 autofocusing algorithms under bright field illumination: a) Normalized Variance (VAR), b) Tenengrad Gradient (TEN), c) DB06 wavelet filter (DB06), d) Fast Fourier Transform (FFT), e) Standard Deviation (STD) and f) Sum Modulus Difference (SMD). In the study, all the...
In this paper, our efforts focus on the downscaling problem in the framework of surface soil moisture. Our purpose is to introduce a new methodology to transform low-resolution remote sensing data (for example from a satellite) about soil moisture to higher resolution information that contains better information for use in hydrologic studies or water management decision making. Our goal is to obtain...
In publishing and printing of network version field, there are enormous number of TIFF format (CMYK) images which requires too huge space for storing and enough bandwidth for transmitting. Therefore, common need to manipulate huge amount of data brought about the issue of fast lossless compression. 2D integer wavelet transform can be used for lossless compression of static image, such as, 5/3 lifting...
The objective of this paper is to evaluate the classification performance of several feature extraction and classification methods for exotic wood texture images as dataset. The Gray Level Co-occurrence Matrix, Local Binary Patterns, Wavelet, Ranklet, Granulometry, and Laws' Masks will be used to extract features from the images. The extracted features are then fed into five classification techniques:...
Device identification is an emerging field where technologies used to create a digital image are inferred by strategic image analysis. Some of the more well understood topics in this area include techniques to identify cameras, scanners and printers. The goal of printing-imaging cycle device identification is to gather information about the printing and imaging devices used to create, then digitally...
In this paper, a new method of insulator fault detection by texture feature sequence is proposed. Morphology, Hough transform line detection and statistic texture feature are applied to this method. Because there are some noises during image shooting, it is necessary that the insulator image should be preprocessed and corrected. The preprocessing includes image grayness, image enhancement and morphological...
In this paper, we manage to use the clustering method realize sonar image segmentation. A particle swarm optimization (PSO) based FCM algorithm (PSO-FCM) is proposed which PSO incorporate with Fuzzy Clustering Method(FCM). The algorithm takes the clustering result of PSO as the initialization of the FCM, and uses fuzzy measures and fuzzy integrals to express the adapt function. At last, the algorithm...
Accurate extraction of prostate biopsy samples during Transectal Ultra Sound (TRUS) guided prostate biopsy is facilitated with the registration of pre-acquired Magnetic Resonance (MR) images with the Ultrasound (US) images. This paper proposes a novel method of generating optimal correspondences to register the MR and US images using Thin-Plate Splines (TPS) transformation. The correspondence generation...
Optical Character Recognition (OCR) converts images of handwritten or printed text captured by camera or scanner into editable text. OCR has seen limited adoption in mobile platforms due to the performance constraints of these systems. Intel® Atom™ processors have enabled general purpose applications to be executed on handheld devices. In this paper, we analyze a reference implementation of the OCR...
The aim of this study is to extract homogenous and edge regions from a post-earthquake Quickbird satellite image with high resolution and to combine this spatial information with spectral information in classification of earthquake damage. In order to extract the homogenous and edge regions from the image, a spatial filtering approach and Canny filter were used. A novel method called support vector...
This paper explores the use of Two-Dimensional Robust Neighborhood Discriminant Embedding (2D-RNDE) as a means to improve the performance and robustness of face recognition. 2D-RNDE is based on graph embedding framework and Fisher's criterion, it can utilize the original two-dimensional image data directly and takes into account the Individual Discriminative Factor (IDF) which is proposed to describe...
This paper describes a new automatic image segmentation strategy for segmenting green plants. The final goal is its application in Precision Agriculture. The goal is to identify several classes of greenness coming from the plants. We exploit the performance of several existing approaches so that conveniently combined allow us to design the automatic approach based on non automatic methods. First we...
This paper constructs a fuzzy contrast enhancement algorithm and then combination with mathematical morphology to improve the fog blurred images which captured in bad weather. In this algorithm, we improve the membership function of fuzzy domain and its inverse operation. Meanwhile, we define a new more effective function which can calculate the pixel gray membership function after enhanced. Experimental...
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