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Image edge detection plays an important role in the system of computer vision. Wavelet is a powerful tool in image processing and has wide application to edge detection for its multiscale characteristic. Based on wavelet modulus maximum edge detection algorithm, an improved method is proposed in this paper, which gives an automatic determination function of eliminateing noise threshold by using the...
Vectorization of the lattice diagram after contour segmentation is a critical techniqure to keep tufted carpet from destortion in the process of manipulator-tufting. A new algorithm is put forward to realize the vectorization, and keep the fitting error in an allowable range. The process of curve vectorization includes several steps: Form a feature point set by extracting the Freeman chain coding...
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...
In this paper, a novel fast logo detection approach in document images is presented. Logos with separated parts usually can affect the logo detection process. To overcome this problem, some specifications of logos are considered. Our proposed method divided in three main sections. In the first section, a horizontal dilation operator is used to merge separated parts of logo in horizontal direction...
We introduce a non-kinematic based approach to autonomous target tracking using a new set of Independent and Indirectly Generated Attributes (IIGA) from hyperspectral imagery. The IIGA method addresses the detection of rare signal appearance (i.e., targets represented by a few pixels), which is often the case in remote sensing target tracking. The proposed method demonstrates that object distinctness...
With the development of the Broadcasting and Video network, the Monitoring System on Digital Video Broadcasting is becoming more and more important. Image recognition technology is widely applied to detect the degraded video in the television observation system. Mosaic block easily occurs in the TV signals, which will degrade the video quality. The conventional mosaic detection algorithm can't distinguish...
An adaptive fuzzy c-means (AFCM) clustering based algorithm was developed and applied to the segmentation and classification of multi-color fluorescence in situ hybridization (M-FISH) images, which can be used to detect chromosomal abnormalities for cancer and genetic disease diagnosis. The algorithm improves the classical fuzzy c-means (FCM) clustering algorithm by introducing a gain field, which...
This paper presents a unified framework aimed at detecting unstained living cells in bright-field (BF) microscopy and finding suitable microinjection points within their surface. Automatic localization of cells is a critical step in improving the procedure of microinjection that, so far, is still conducted manually by trained operators. This work compares different state of the art image processing...
Video search today uses the metadata surrounding the video, ignoring its semantic content. Over the years, a lot of research has gone into indexing and browsing of sports video content. In this work, we present a novel approach for classification of events in cricket videos and thus, summarize its visual content. The proposed method segments a cricket video into shots and identifies the visual content...
A high rate of expression of Endothelin protein in the placental cell is very much regulated by inhalation of tobacco smoke and leads to placental abnormalities subjected to birth failure. Our application developed using Image Processing, Nearest Neighbor algorithm (NN) and Genetic Algorithms (GA), automates the study of these proteins to assist pathologists and lab technicians in achieving a more...
This paper presents adaboost based disguised face discrimination method on embedded devices. The introduced method is simple and fast method for face detection and disguised face discrimination for security purpose.
The paper proposes a novel method to compress color images with imperceptible quality loss. The algorithm explores the difference in error perceptibility of human visual system for various areas. It is done by implementing different non-uniform quantizers for flat, detail and random blocks of pixels. These blocks are classified based on principle component analysis (PCA) and prediction error. For...
Stereoscopic video object segmentation plays an important role in stereo vision analysis and application. In this paper, we proposed the combination support vector machine (SVM) and mean shift clustering algorithm to achieve classification and segmentation of stereoscopic video. We firstly divided the left image of stereoscopic video into the two classes of target and background and perform training...
This paper presents an algorithm for localization and classification of subtitles in TV videos. We extend an existing static-region detector with object-based adaptive filtering and binary classification of subtitle bounding boxes, using geometry and text-stroke alignment features. Compared to this static-region detector, we reduce the number of falsely detected subtitle pixels by a factor of 20,...
For distinguish the LSB (Least significant bit) replacement stego image from MLSB (Multiple least significant bits) stego image, which are two typical kinds of steganographical methods of image spatial domain and have been applied widely, a classification algorithm based on the shift of pixel value and irrelevance of pixel pairs is proposed. In this algorithm, a shift operator is adopted for each...
This paper describes a novel approach to the connected component labeling problem, derived from two fast labeling algorithms, Wu et al. and Park et al. We propose a method that improves over existing divide and conquer methods. We propose two new methods - First, hierarchical (coarse to fine) label propagation from various sub images. Second, the recursive boundary labeling method is only one neighbor...
In this paper, a new classification scheme of fully polarimetric SAR images is proposed. This is based on the joint use of the Freeman-Durden decomposition and generalized discriminant analysis, a new method for Feature extraction. After getting the powers of the three scattering mechanism components through Freeman-Durden decomposition, the Feature extraction algorithm is introduced to well exploit...
Airborne Light Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy...
Segmentation of an image into its components plays an important role in most of the image processing applications. In this article an important application of image processing in determination of apple quality is studied, and an automatic algorithm is proposed in order to determine apples skin color defects. First, this image is converted from RGB to color space L∗ a∗ b∗. Then fruit shape is extracted...
Based on a recent proposed and popular sparse representation based classifier (SRC), in this paper we presented a novel Learning Sparse Representation based Clustering (LSRC) scheme for Synthetic Aperture Radar (SAR) segmentation. LSRC introduces the examples-based dictionary learning technology in SRC to find a dictionary that is adaptable to sparsely representing samples, which is liable to provide...
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