AN EDGE DETECTOR BA SED ON WAVELET TRANSFORM FOR SAR IMAGE

Edge detecting is a f undamental issue in image analysis and image processing. In this paper, based on wavelet transform, an edge detector of SAR image is studied to serve the image aided navigation. Though wavelet transform is efficient as an edge detector, a l ot of false edges will be extracted from a SAR image, especially in areas of hig h reflectivity, with wavelet transform and a fixed threshold because SAR images are always contaminated by speckle. Therefore, this paper develops an algorithm by using a variable threshold with constant false alarm rates to help suppressin g the speckle in SAR images. Finally, two simulating tests are given and the res ults show that the effect of the multiplicative speckle is controlled and there are few false edges in the gotten edge images. Moreover, owing to the threshold from the wavelet transform coefficients, the algorithm can assure the real time of SAR image aided navigation.

Detection of text in images using SUSAN edge detector

Text embedded in images is one of many important cues for indexing and retrieval of images and videos. In the paper, we present a novel method of detecting text aligned either horizontally or vertically, in which a pyramid structure is used to represent an image and the features of the text are extracted using SUSAN edge detector. Text regions at each level of the pyramid are identified according to the autocorrelation analysis. New techniques are introduced to split the text regions into basic ones and merge them into text lines. By evaluating the method on a set of images, we obtain a very good performance of text detection.

2-D MULTIRATE ALGORITHMS FOR EFFICIENT IMPLEMENTATION OF EDGE DETECTION

Edge detection is a fundamental issue in image analysis. This paper proposes multirate algorithms for efficient implementation of edge detector, and a design example is illustrated.The multirate (decimation and/or interpolation) signal processing algorithms can achieve considerable savings in computation and storage. The proposed algorithms result in mapping relations of their z-transfer functions between non-multirate and multirate mathematical expressions in terms of time-varying coefficient instead of traditional polyphase decomposition counterparts.The mapping properties can be readily utilized to efficiently analyze and synthesize multirate edge detection filters. The Very high-speed Hardware Description Language (VHDL) simulation results verify efficiency of the algorithms for real-time Field Programmable Gate-Array (FPGA)implementation.

Edge Detection Algorithm of SAR Images with Wedgelet Filter

Based on the analysis of the characteristics of synthetic aperture radar （SAR） images, a new edge detection method is proposed. The wedgelet transform is introduced into the area of SAR image speckle reduction for it can provide a nearly optimal representation for images in the horizon class. The wedgelet filter has good ability in keeping edge and speckle reduction. Then, a ratio edge detector is applied after a process of speckle reduction. The experimental results show that the method outperforms substantially others visually.

Pyramidal Edge Detection Method Based on AWFM Filtering and Fuzzy Linking Model

A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to fine edge detection. The validation experiment results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector andprevious multiresolution approach, especially in impulse noise environment.

Robust Interactive Method for Hand Gestures Recognition Using Machine Learning

The Hand Gestures Recognition(HGR)System can be employed to facilitate communication between humans and computers instead of using special input and output devices.These devices may complicate communication with computers especially for people with disabilities.Hand gestures can be defined as a natural human-to-human communication method,which also can be used in human-computer interaction.Many researchers developed various techniques and methods that aimed to understand and recognize specific hand gestures by employing one or two machine learning algorithms with a reasonable accuracy.Thiswork aims to develop a powerful hand gesture recognition model with a 100%recognition rate.We proposed an ensemble classification model that combines the most powerful machine learning classifiers to obtain diversity and improve accuracy.The majority voting method was used to aggregate accuracies produced by each classifier and get the final classification result.Our model was trained using a self-constructed dataset containing 1600 images of ten different hand gestures.The employing of canny’s edge detector and histogram of oriented gradient method was a great combination with the ensemble classifier and the recognition rate.The experimental results had shown the robustness of our proposed model.Logistic Regression and Support Vector Machine have achieved 100%accuracy.The developed model was validated using two public datasets,and the findings have proved that our model outperformed other compared studies.

EFFICIENT IMPLEMENTATION OF 3D FILTER FOR MOVING OBJECT EXTRACTION

In this paper the design and implementation of Multi-Dimensional (MD) filter, particularly 3-Dimensional (3D) filter, are presented. Digital (discrete domain) filters applied to image and video signal processing using the novel 3D multirate algorithms for efficient implementation of moving object extraction are engineered with an example. The multirate (decimation and/or interpolation) signal processing algorithms can achieve significant savings in computation and memory usage. The proposed algorithm uses the mapping relations of z-transfer functions between non-multirate and multirate mathematical expressions in terms of time-varying coefficient instead of traditional polyphase de- composition counterparts. The mapping properties can be readily used to efficiently analyze and synthesize MD multirate filters.

A new algorithm of brain volume contours segmentation

This paper explores brain CT slices segmentation technique and some related problems, including contours segmentation algorithms, edge detector, algorithm evaluation and experimental results. This article describes a method for contour-based segmentation of anatomical structures in 3D medical data sets. With this method, the user manually traces one or more 2D contours of an anatomical structure of interest on parallel planes arbitrarily cutting the data set. The experimental results showes the segmentation based on 3D brain volume and 2D CT slices. The main creative contributions in this paper are: (1) contours segmentation algorithm; (2) edge detector; (3) algorithm evaluation.

Computer-Aided Detection System on Tangled Roller

The mechanical-touched detector was used commonly in textile production limes. It has some defect with high false alarm rate, response delay and high maintenance cost. In order to overcome such defects, a new kind device was developed and used to detect roller tangled in the production lines. It is based on image processing. The core algorithm was composed of Canny edge detection, removing interference, detection of perpendicularity line and detection of broken tow. After the four steps, the broken tow could be recognized quickly and correctly. The algorithm is robust and high efficiency. So, the detection device has characteristic of stable, quickly-response and low maintains cost. It can keep superiority with long lifespan even in more formidable conditions. It guarantees a safe and stable production condition.

Study of the photon identification efficiency with ALICE photon spectrometer

The efficiency for the detection and identification of photons with the ALICE PHOton Spectrometer PHOS has been studied with the Monte-Carlo generated data. In particular, the influence on the efficiency of the PHOS-module edge-effect and of the material in front of PHOS have been examined.