Gray Histogram Research Articles

Fuzzy Domain Image Segmentation Based on Space Information

Synthetic aperture radar (SAR) Image containing the coherent speckle noise, traditional methods can't very well to SAR image segmentation, based on SAR image grayscale distribution model, this paper proposes a combination of pixel gray level and area information of the image segmentation method. First of all, based on SAR image in all kinds of feature of gray histogram presents the facts of the Rayleigh distribution, fitting of image gray level of probability density distribution; Then use fuzzy biggest office methods select the optimal threshold, and the resulting statistics as the related parameters of image, the image blur ; Then to 3 x3 neighborhood pixels within the membership degree of fuzzy characteristics of Kohonen self-organizing map neural network is adopted to improve the coarse segmentation, the segmentation of noise and boundary classes pixels using a region growing technique relaxation iteration to fine segmentation.

Coal–rock interface detection on the basis of image texture features

Based on the stability and inequality of texture features between coal and rock, this study used the digital image analysis technique to propose a coal–rock interface detection method. By using gray level co-occurrence matrix, twenty-two texture features were extracted from the images of coal and rock. Data dimension of the feature space reduced to four by feature selection, which was according to a separability criterion based on inter-class mean difference and within-class scatter. The experimental results show that the optimized features were effective in improving the separability of the samples and reducing the time complexity of the algorithm. In the optimized low-dimensional feature space, the coal–rock classifier was set up using the fisher discriminant method. Using the 10-fold cross-validation technique, the performance of the classifier was evaluated, and an average recognition rate of 94.12% was obtained. The results of comparative experiments show that the identification performance of the proposed method was superior to the texture description method based on gray histogram and gradient histogram.

A semi-supervised learning approach for detection of phishing webpages

This paper proposes a new phishing webpage detection approach based on a kind of semi-supervised learning method-transductive support vector machine (TSVM). Firstly the features of web image are extracted for complementing the disadvantage of phishing detection only based on document object model (DOM); they include gray histogram, color histogram, and spatial relationship between subgraphs. Then the features of sensitive information are examined by using page analysis based on DOM objects. In contrast to the drawback of support vector machine (SVM) algorithm which simply trains classifier by learning little and poor representative labeled samples, this method introduces the TSVM to train classifier that it takes into account the distribution information implicitly embodied in the large quantity of the unlabeled samples, and have better performance than SVM. The experimental results show that the proposed method not only achieves better classification accuracy, but also has strong applicability as the independent method of phishing detection.

Gray scale histogram analysis of solid breast lesions with ultrasonography: can lesion echogenicity ratio be used to differentiate the malignancy?

PurposeThe aim of this study was to investigate the diagnostic performance of lesion echogenicity ratios (LER) calculated by image histogram analysis for distinction of malignant and benign breast lesions. Material and methodsA total of 55 patients (mean age, 44 years) with 59 lesions were included. Ultrasound images were analyzed retrospectively. ResultsMean LER values in benign and malignant lesions were 1.63±0.41 and 3.1±0.87, respectively. The difference between LER values of benign and malignant breast lesions was statistically significant (P<.001). ConclusionLER can be used as an adjunct ultrasound parameter to differentiate between benign and malignant breast lesions.

Adaptive all-season image tag ranking by saliency-driven image pre-classification

Social image tag ranking has emerged as an important research topic due to its application on web image search. This paper presents an adaptive all-season tag ranking algorithm which can handle the images with and without distinct object(s) using different tag ranking strategies. Firstly, based on saliency map derived from the visual attention model, a linear SVM is trained to pre-classify an image as attentive or non-attentive category by using the gray histogram descriptor on the corresponding saliency map. Then, an image with distinct object is processed by the tag saliency ranking algorithm emphasizing distinct object, which combines image saliency map with sparse representation based multi-instance learning algorithm. On the other hand, an image without distinct object can be processed by the tag relevance ranking algorithm via the sparse representation based neighbor-voting strategy. Such adaptive all-season tag ranking strategy can be regarded as taking full advantage of existing tag ranking paradigms. Experiments conducted on well-known image data sets demonstrate the effectiveness of the proposed framework.

A Seamless Approach to Stitching Lunar DOMs with TPS

Aiming at the mosaic technology of the orthophoto acquired by Chinese remote sensing satellite CE-1, a thin-plate spline (TPS) function based method of image mosaic is proposed while the traditional mosaic method seems impossible. With the advantages of TPS (Thin-plate Spline) function in image transformer, the image fusion technology is introduced to get the seamless image mosaic result. Considering the mosaic result of lunar DOMs (Digital Orthophoto Map) by CE-1, a sharp gray jump usually exists beside the stitching line. To solve the uneven gray distribution caused by light changing or position difference during photographing, a method is described which is based on dynamic rules to stretch image according to the gray histogram. Using CE-1's 2C data, the experimental result states that our approach can guarantee the accuracy of the geographical precision and can greatly meet the needs of seamless mosaic with good visual effect.

Moving object tracking with related multi-regions based on Kalman filter

A moving object tracking algorithm with related multi-regions based on Kalman filter was proposed to solve the occlusion and tracking excursion.Through locating multiple regions on the target and constructing undirected graphs,the algorithm calculated the predicted position of the center of each region by using Kalman filter firstly.Then by combining gray histogram match with positional relations of adjacent regions,it calculated the observation center of each region.At last,it realized tracking by revising the observation centers using Kalman filter.The experimental results of human tracking of two regions show that the proposed algorithm has better robustness and real-time performance than the result of tracking each region using Mean Shift algorithm under the occlusion or similar targets and backgrounds.

Normalized SAD Method for Chinese Document Image Registration

In the area of digital content technologies, Chinese document image registration is an important task of document mosaic system, also an important research content of distorted document recognition system. The Sum of Absolute Difference, SAD, is a similarity criterion for image registration. To get better document image registration accuracy, a document image registration method based on normalized SAD is proposed. In this method, a pre-processing procedure is performed to identify the inflection point for the normalized SAD registration. Then gray histogram of the matched image is normalized firstly so that the different laminations of the two document image can be eliminated. Then the two document images are registered by the SAD method. At last, a post-processing of the normalized SAD registration method is performed to the two registered document images so that the two distorted document images can be mosaiced together and get a flatter document image. Experimental results show that the document image registration method based on normalized SAD is more robust than the classical SAD method and the Optical Character Recognition (OCR) rate of the new mosaiced image is markedly higher than the two original distorted document images.

Counter-forensics of SIFT-based copy-move detection by means of keypoint classification

Abstract Copy-move forgeries are very common image manipulations that are often carried out with malicious intents. Among the techniques devised by the ‘Image Forensic’ community, those relying on scale invariant feature transform (SIFT) features are the most effective ones. In this paper, we approach the copy-move scenario from the perspective of an attacker whose goal is to remove such features. The attacks conceived so far against SIFT-based forensic techniques implicitly assume that all SIFT keypoints have similar properties. On the contrary, we base our attacking strategy on the observation that it is possible to classify them in different typologies. Also, one may devise attacks tailored to each specific SIFT class, thus improving the performance in terms of removal rate and visual quality. To validate our ideas, we propose to use a SIFT classification scheme based on the gray scale histogram of the neighborhood of SIFT keypoints. Once the classification is performed, we then attack the different classes by means of class-specific methods. Our experiments lead to three interesting results: (1) there is a significant advantage in using SIFT classification, (2) the classification-based attack is robust against different SIFT implementations, and (3) we are able to impair a state-of-the-art SIFT-based copy-move detector in realistic cases.

Measurement of particle size based on digital imaging technique

To improve the analysis methods for the measurement of the sediment particle sizes with a wide distribution and of irregular shapes, a sediment particle image measurement, an analysis system, and an extraction algorithm of the optimal threshold based on the gray histogram peak values are proposed. Recording the pixels of the sediment particles by labeling them, the algorithm can effectively separate the sediment particle images from the background images using the equivalent pixel circles with the same diameters to represent the sediment particles. Compared with the laser analyzer for the case of blue plastic sands, the measurement results of the system are shown to be reasonably similar. The errors are mainly due to the small size of the particles and the limitation of the apparatus. The measurement accuracy can be improved by increasing the Charge-Coupled Devices (CCD) camera resolution. The analysis method of the sediment particle images can provide a technical support for the rapid measurement of the sediment particle size and its distribution.

A multi-class bi-level thresholding method for accurate anthropometric measurements of scanned plantar images

Traditionally, the anthropometric measurements of foot or insole were taken manually by an anthropometrist for clinical and sporty purposes. Digital foot scanners have been developed in recent years to yield anthropometrists digital image of plantar with pressure distribution and anthropometric information. In this paper, an automated thresholding method based on Shanbag entropy and the weighted gray level spatial correlation histogram is presented for analysis of scanned foot images. The presented method compared with traditional two-dimensional histogram and other single-class-based methods automatically accurately detects the foot edges and areas. Also, by background removal, it attains a perfect foot image while in which white pixels of the resulting thresholded image correspond to the points of the scanner which detects pressure and on the contrary the black pixels correspond to background. We are taking into accounts the image’s local properties along with its global properties in a fuzzy domain by employing weighted gray level spatial correlation histogram (W-GLSC). First, a three-dimensional histogram based on the statistics of the gray levels’ probability and similarity with neighboring pixels (GLSC histogram) is weighted by the membership values assigned by Jawahar clustering method for foreground–background discrimination. Then, the Shanbag entropy is used to maximize the information transfer from the original image to the resulting thresholded image. Resulting binary images are undergone anthropometric measurements by considering the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper.

基于激光散斑的涂料干燥过程实时监测技术

The basic principles based on dynamic characteristics of laser speckle for monitoring of the paint drying process was studied.The processing algorithms of real-time detection were analyzed.A difference-average algorithm of dynamic speckle was proposed.In this algorithm,gray distribution histogram of the difference image was used to qualitatively describe the strength of the dynamic characteristics of the laser speckle,and the average gray level of the difference image was used to quantitative describes the changes of speckle.Experimental results show that dynamic characteristics of speckle can be used to non-destructive and on-line monitor the paint drying process,and the difference-average algorithm can be given real-time results in the monitoring process with shorter computation time and lower hardware requirements.

Enhancement of images using various histogram equalization techniques

Image enhancement is a mean as the improvement of an image appearance by increasing dominance of some features or by decreasing ambiguity between different regions of the image. Image enhancement processes consist of a collection of techniques that seek to improve the visual appearance of an image or to convert the image to a form better suited for analysis by a human or machine. Various enhancement schemes are used for enhancing an image which includes gray scale manipulation, filtering and Histogram Equalization (HE). Histogram equalization is one of the well known image enhancement technique. It became a popular technique for contrast enhancement because this method is simple and effective. This paper presents a review of histogram equalization techniques for image enhancement.

Research of the Terminal Timer System Based on High-Speed Color Linear CCD

In competitive sporting events, the scores confirm replied on manual timing can’t satisfy the requirements, according to the provisions of the IAAF, the major sports event will require the use of electric timing system. At present, the development level of the photo finish collecting still stay in the black-and-white image level, high-speed color linear CCD array technology used in track events final electrical-timing system, carried out in-depth analysis of the various factors that affect image quality of the post-processing, described in digital image processing with gray technology , color balance, histogram equalization and digital image processing techniques so as to get clear, high quality color image data.

An improved [formula omitted]-means clustering algorithm for fish image segmentation

Fish contour extraction from images is the foundation of many fish image applications such as disease early warning and diagnostics, animal behavior, aquatic product processing, etc. In order to improve the accuracy and stability of fish image segmentation, we propose a new fish images segmentation method which is the combination of the K-means clustering segmentation algorithm and mathematical morphology. Firstly, the traditional K-means clustering segmentation algorithm has been improved for fish images. The best number of clusters is determined by the number of gray histogram peaks, and the cluster centers data is filtered by comparing the mean with the threshold decided by Otsu. Secondly, the opening and closing operations of mathematical morphology are used to get the contour of the fish body. The experimental results show that the algorithm realized the separation between the fish image and the background in the condition of complex backgrounds. Compared with Otsu and other segmentation algorithms, our algorithm is more accurate and stable.

Detecting and tracking dim small targets in infrared image sequences under complex backgrounds

This paper presents a unified framework for automatically detecting and tracking dim small targets in infrared (IR) image sequence under complex backgrounds. Firstly, the variance weighted information entropy (variance WIE) followed by a region growing technique is introduced to segment the candidate targets in a single-frame IR image after background suppression. Then the pipeline filter is used to verify the real targets. The position and the size of the detected target are then obtained to initialize the tracking algorithm. Secondly, we adopt an improved local binary pattern (LBP) scheme to represent the target texture feature and propose a joint gray-texture histogram method for a more distinctive and effective target representation. Finally, target tracking is accomplished by using the mean shift algorithm. Experimental results indicate that the proposed method can effectively detect the dim small targets under complex backgrounds and has better tracking performance compared with the gray histogram based tracking methods such as the mean shift and the particle filtering.

Robust wood species recognition using variable color information

In this paper, we propose a robust wood species classification scheme using color wood surface images. First, a novel 2D wood image measurement machine is devised, and the wood RGB color image is converted into a combined gray scale image. Second, the corresponding gray histogram is established, which will be used as the classification feature. Third, an improved snake model is used to fulfill the curve deformation of the histogram curve of the standard specimen. This snake will then converge to the histogram curve of the test specimen. Finally, pattern recognition is performed by comparing the initial and final snakes with the histogram curve of the test specimen. We have experimentally proved that this scheme improves the recognition accuracy, which can efficiently discriminate the intraspecific color variation and the interspecific color variation.

Word Extraction from Speech Recognition using Correlation Coefficients

is the fundamental way of communicating with one another. It simply refers to transmission of messages. In case of speech production the information is transmitted in the form of analog waveform that can be transmitted, recorded or decoded. A number of algorithms for speech recognition have been proposed. In this paper, we have suggested an innovative approach of speech recognition. We have initially stored some voice in the database where the same speaker has told different words. Then we have inputted a sample voice of the same person through the microphone where he is speaking a specific word which is already stored in the database. We have performed the task of similar word recognition by finding the gray scale image and histogram plot of inputted word and finally we have used the correlation coefficient for making comparison between two words.

Reconstruction of internal structures and numerical simulation for concrete composites at mesoscale

At mesoscale, concrete is considered as a three-phase composite material consisting of the aggregate particles, the cement matrix and the interfacial transition zone (ITZ). The reconstruction of the internal structures for concrete composites requires the identification of the boundary of the aggregate particles and the cement matrix using digital imaging technology followed by post-processing through MATLAB. A parameter study covers the subsection transformation, median filter, and open and close operation of the digital image sample to obtain the optimal parameter for performing the image processing technology. The subsection transformation is performed using a grey histogram of the digital image samples with a threshold value of [120, 210] followed by median filtering with a square module based on the dimensions of the aggregate particles and their internal impurity. We then select a disk tectonic structure with a specific radius, which performs open and close operations on the images. The edges of the aggregate particles (similar to the original digital images) are obtained using the canny edge detection method. The finite element model at mesoscale can be established using the proposed image processing technology. The location of the crack determined through the numerical method is identical to the experimental result, and the load-displacement curve determined through the numerical method is in close agreement with the experimental results. Comparisons of the numerical and experimental results show that the proposed image processing technology is highly effective in reconstructing the internal structures of concrete composites.

The Gray Processing of Moon Digital Orthophoto Map

Considering the mosaic result of the lunar DOM (Digital Orthophoto Map) produced by China's “CE-1” satellite, there usually exists a sharp gray jump beside the joining line. As to a strip image, the gray distribution may be uneven because of the light changing or position difference during photographing. To solve these matters, a method was proposed which is based on dynamic rules to detect the best joining line, and then stretch image according to its gray histogram. By making the pixels around boundary to change gradually, the joining line will finally be invisible. In order to solve the uneven gray distribution problems causing by imaging angle, light condition and other factors, a homogenization technology based on statistics of gray distribution was proposed. Using statistical information of the bands’ longitudinal changes to united the gray level to a defaulted range. The experimental results show that the method of this paper can make the integral gray level become even, the transition become more gently, and visual effect become more natural.