Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

240 nm AlGaN-based deep ultraviolet micro-LEDs:size effect versus edge effect

240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge effects.Here,it is revealed that the peak optical output power increases by 81.83%with the size shrinking from 50.0 to 25.0μm.Thereinto,the LEE increases by 26.21%and the LEE enhancement mainly comes from the sidewall light extraction.Most notably,transversemagnetic(TM)mode light intensifies faster as the size shrinks due to the tilted mesa side-wall and Al reflector design.However,when it turns to 12.5μm sized micro-LEDs,the output power is lower than 25.0μm sized ones.The underlying mechanism is that even though protected by SiO2 passivation,the edge effect which leads to current leakage and Shockley-Read-Hall(SRH)recombination deteriorates rapidly with the size further shrinking.Moreover,the ratio of the p-contact area to mesa area is much lower,which deteriorates the p-type current spreading at the mesa edge.These findings show a role of thumb for the design of high efficiency micro-LEDs with wavelength below 250 nm,which will pave the way for wide applications of deep ultraviolet(DUV)micro-LEDs.

Saliency detection and edge feature matching approach for crater extraction

Craters are salient terrain features on planetary surfaces, and provide useful information about the relative dating of geological unit of planets. In addition, they are ideal landmarks for spacecraft navigation. Due to low contrast and uneven illumination, automatic extraction of craters remains a challenging task. This paper presents a saliency detection method for crater edges and a feature matching algorithm based on edges informa- tion. The craters are extracted through saliency edges detection, edge extraction and selection, feature matching of the same crater edges and robust ellipse fitting. In the edges matching algorithm, a crater feature model is proposed by analyzing the relationship between highlight region edges and shadow region ones. Then, crater edges are paired through the effective matching algorithm. Experiments of real planetary images show that the proposed approach is robust to different lights and topographies, and the detection rate is larger than 90%.

Study on Edge Extraction Methods for Image-based Icing On-line Monitoring on Overhead Transmission Lines

A new method of measuring the icing thickness of transmission lines on-line is proposed in this paper.In this method,the pictures of transmission lines which are photoed by the camera on the iron tower are processed immediately to extract the edges of the transmission line conductor and transmission line insulators.The icing thickness can be gained by comparing the edges of the iced transmission line and the uniced one.Two icing image edge extraction methods are described in detail,that is,a method based on the combination of the wavelet transform and the floating threshold method and a method based on the combination of the optimal threshold method and the mathematical morphology transform.The icing images from the artificial climatic chamber and transmission lines are used to test the methods above.The results show that the method based on the wavelet transform and the floating threshold method does well in the extraction of relatively smooth edges,such as glaze icing on conductor and icing on the insulator;meanwhile,the method based on the optimal threshold method and the mathematical morphology transform does well in the edge extraction of icing on the conductor,especially the opaque rime icing on the conductor with complicated edges.

A LUMINANCE EDGE EXTRACTION METHOD USING GRADIENT OF GRAY LEVEL FOR SYNTHETIC APERTURE RADAR IMAGERY

In the multistage imaging processing for SAR digital imaging and applications ofSAR imagery,extraction of luminance edge for the SAR imageis often required.It is well studiedto extract the luminance edge for ordinary images,The methods using gradient are effective andcommonly used.Because of the serious noise of coherent speckle exists in SAR images,somepeople believe that edge extraction by using gradient for SAR imagery gives poor results.Inthis paper,we have derived a rather ideal method for the extraction of luminance edge for SARimagery with the consideration of the characteristics of SAR imagery.This method uses therelative average gradient and combines detection with tracking.

Edge Contour Extraction in MR Image Using Edgeflow Contour Model

This paper presents a new model for edge extraction of MR images, based on curve evolution and edgeflow techniques. At first the model for curve evolution is constructed, which automatically detect boundaries, and change of topology in terms of the edgeflow fields, and then the numerical approximation of the model is introduced, which is based on semi-implicit scheme to speed up the proposed approach. Finally, the numerical implementation is present and the experimental results show that the proposed model successfully extracts the edge contours, regardless of the heavy noise.

Underwater Sea Cucumber Target Detection Based on Edge-Enhanced Scaling YOLOv4

Sea cucumber detection is widely recognized as the key to automatic culture.The underwater light environment is complex and easily obscured by mud,sand,reefs,and other underwater organisms.To date,research on sea cucumber detection has mostly concentrated on the distinction between prospective objects and the background.However,the key to proper distinction is the effective extraction of sea cucumber feature information.In this study,the edge-enhanced scaling You Only Look Once-v4(YOLOv4)(ESYv4)was proposed for sea cucumber detection.By emphasizing the target features in a way that reduced the impact of different hues and brightness values underwater on the misjudgment of sea cucumbers,a bidirectional cascade network(BDCN)was used to extract the overall edge greyscale image in the image and add up the original RGB image as the detected input.Meanwhile,the YOLOv4 model for backbone detection is scaled,and the number of parameters is reduced to 48%of the original number of parameters.Validation results of 783images indicated that the detection precision of positive sea cucumber samples reached 0.941.This improvement reflects that the algorithm is more effective to improve the edge feature information of the target.It thus contributes to the automatic multi-objective detection of underwater sea cucumbers.

Tip-Edge Plus与Damon托槽对拔牙病例前牙转矩控制的比较

目的:比较Damon自锁托槽与Tip-Edge plus差动直丝弓托槽在拔牙病例中对前牙转矩的控制情况。方法:选取2012~2014年在南京大学附属口腔医院正畸科治疗的拔除4颗前磨牙的患者,分别采用Tip-Edge plus差动直丝弓矫治技术(TP组)和Damon自锁托槽(DM组)矫治技术完成治疗,各20例;拍摄数字化头颅侧位片,测量分析患者治疗前后的变化。结果:治疗前,上颌切牙倾斜度(U1-SN°)两组没有明显差异[TP组(112.45±6.39)°,DM组(111.87±6.33)°];正畸治疗后前牙明显内收,两组上前牙转矩无统计学差异[TP组和DM组分别为(99.32±7.33)°和(99.57±4.74)°];治疗后上下唇突度显著减小,侧貌明显改善,Z角两组之间没有显著差异[TP组和DM组分别为(66.74±10.3)°和(68.11±9.54)°]。结论:Damon自锁托槽与Tip-Edge plus托槽在拔牙病例中都能有效的控制前牙转矩,两组间无明显差异。

利用Tip-Edge第一期矫治技术非拔牙矫治安氏Ⅱ类1分类错的临床研究

目的:应用Tip-Edge I期矫治技术对治疗非拔牙安氏Ⅱ类1分类错进行矫治,并对矫治机理进行探讨。方法:临床筛选病例12例。矫治前后拍摄头颅侧位定位片,并对相关指标进行模型测量。治疗前后相关头影测量项目测量值输入计算机,用SAS软件包对各测量值进行配对t检验。结果:Tip-Edge I期矫治结束后,上颌切牙倾斜(U1-SN,U1-Apog)明显减小,而下颌切牙的倾斜明显增加(P<0.01)覆牙合超显著减小。上颌第一磨牙远中移动1.5 mm,远中直立3.5°,有显著性差别。模型测量分析表明上颌尖牙间宽度和磨牙宽度显著增加。下颌尖牙间的宽度无显著变化。下颌磨牙宽度显著增加。结论:利用Tip-Edge I期技术能够非拔牙矫治处于生长发育期的安氏Ⅱ类1分类错。对处于生长发育期具有良好生长型(水平生长型)和生长潜力的患者较易取得良好的效果。

Edge Effect Correction in the S-A Method for Geochemical Anomaly Separation

Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and holes (with missing data) often causes frequency distribution distortion in the frequency domain. For example, bright strips are commonly seen in frequency distribution when using a Fourier transform. Such edge effect distortion may affect information extraction results; sometimes severely, depending on the edge abruptness of the image. Traditionally, edge effects are reduced by smoothing the image boundary prior to applying a Fourier transform. Zero-padding is one of the most commonly used smoothing methods. This simple method can reduce the edge effect to some degree but still distorts the image in some cases. Moreover, due to the complexity of geoscience images, which can include irregular shapes and holes with missing data, zero-padding does not always give satisfactory results. This paper proposes the use of decay functions to handle edge effects when extracting information from geoscience images. As an application, this method has been used in a newly developed multifractal method (S-A) for separating geochemical anomalies from background patterns. A geochemical dataset chosen from a mineral district in Nova Scotia, Canada was used to validate the method.

Feature fusion method for edge detection of color images

A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected as the features. The four features are combined together as a parameter to detect the edges of color images. Experimental results show that the method can inhibit noisy edges and facilitate the detection for weak edges. It has a better performance than conventional methods in noisy environments.

基于Edge Boxes和深度学习的非限制条件下人脸检测

针对光线、旋转、遮挡、平移等因素对人脸检测结果产生的干扰,提出一种基于Edge Boxes和深度学习相结合的人脸检测算法。首先采用Edge Boxes算法提取出可能存在人脸的边界框,提取边界框中的图像并调整至合适的大小,作为卷积神经网络的输入,然后利用卷积神经网络对提取出的图像进行特征提取和分类,最后利用非极大抑制算法排除多余人脸检测框,得到人脸的准确位置。该算法应用于LFW和Yale B人脸数据库的检测率分别达到98.7%和98.5%,识别单张人脸的时间均小于0.5 s。实验结果表明,该算法在检测率和检测速率方面较传统算法都有了很大的提高,对于遮挡、光照、旋转等干扰具有更强的鲁棒性。

Feature Extraction to Polar Image

Some algorithms of feature extraction in existing literature studied for image processing was the gray image with one-dimensional parameter. However, some feature points’ extraction for three-dimensional color of polar image, such as the color edge extraction, inflection points, and so on, was urgently to be solved a polar color problem. For achieving quickly and accurately the color feature extraction to polar image, this paper proposed a similar region of color algorithm. The algorithm was compared to polar image, and the effect to color extraction was also described by the combination of the proposed and existing algorithms. Moreover, this paper gave the comparison of the proposed algorithm and an existing classical algorithm to extraction of color feature. These researches in this paper provided a powerful tool for polar image classification, color feature segmentation, precise recognition, and so on.

Novel histogram descriptor for global feature extraction and description

A novel histogram descriptor for global feature extraction and description was presented. Three elementary primitives for a 2×2 pixel grid were defined. The complex primitives were computed by matrix transforms. These primitives and equivalence class were used for an image to compute the feature image that consisted of three elementary primitives. Histogram was used for the transformed image to extract and describe the features. Furthermore, comparisons were made among the novel histogram descriptor, the gray histogram and the edge histogram with regard to feature vector dimension and retrieval performance. The experimental results show that the novel histogram can not only reduce the effect of noise and illumination change, but also compute the feature vector of lower dimension. Furthermore, the system using the novel histogram has better retrieval performance.

Development of Automatic Extraction Weld for Industrial Radiographic Negative Inspection

In industrial X-ray inspection, in order to identify weld defects automatically, raise the identification ratio, and avoid processing of complex background, it is an important step for sequent processing to extract weld from the image. According to the characteristics of weld radiograph image, median filter is adopted to reduce the noise with high frequency, then relative gray-scale of image is chosen as fuzzy characteristic, and image gray-scale fuzzy matrix is constructed and suitable membership function is selected to describe edge characteristic. A fuzzy algorithm is adopted for enhancing radiograph image processing. Based on the intensity distribution characteristic in weld, methodology of weld extraction is then designed. This paper describes the methodology of all the weld extraction, including reducing noise, fuzzy enhancement and weld extraction process. To prove its effectiveness, this methodology was tested with 64 weld negative images available for this study. The experimental results show that this methodology is very effective for extracting linear weld.

Text Extraction and Enhancement of Binary Images Using Cellular Automata

Text characters embedded in images represent a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, grayscale values, and complex backgrounds. Existing methods cannot handle well those texts with different contrast or embedded in a complex image background. In this paper, a set of sequential algorithms for text extraction and enhancement of image using cellular automata are proposed. The image enhancement includes gray level, contrast manipulation, edge detection, and filtering. First, it applies edge detection and uses a threshold to filter out for low-contrast text and simplify complex background of high-contrast text from binary image. The proposed algorithm is simple and easy to use and requires only a sample texture binary image as an input. It generates textures with perceived quality, better than those proposed by earlier published techniques. The performance of our method is demonstrated by presenting experimental results for a set of text based binary images. The quality of thresholding is assessed using the precision and recall analysis of the resultant text in the binary image.

Advances in Methods of Surface Water Extraction Based on MODIS Data

In recent years,remote sensing technology has been widely used to distinguish and extract water body information on the surface of land,investigate and analyze surface water resources,monitor and study ecological environment,monitor and assess floods. Remote sensing data provided by MODIS sensor carried on satellites in the United States Earth Observation System（ EOS） have high spatial and temporal resolution and spectral resolution,and images have a wide coverage range and are available for free. Moreover,they can be used for dynamic monitoring of changes in water body area on the earth quickly and efficiently. In this study,based on the analysis of spectral characteristics of water body,the characteristics of MODIS data and the methods of surface water extraction were introduced,and the advantages and disadvantages of various methods of water body extraction were analyzed by the comparison between the practical application effects of these methods.

Fast and Robust DCNN Based Lithography SEM Image Contour Extraction Models

Scanning electron microscope(SEM)metrology is critical in semiconductor manufacturing for patterning process quality assessment and monitoring.Besides feature width and feature-feature space dimension measurements from critical dimension SEM(CDSEM)images,visual inspection of SEM image also offers rich information on the quality of patterning.However,visual inspection alone leaves considerable room of ambiguity regarding patterning quality.To narrow the room of ambiguity and to obtain more statistically quantitative information on patterning quality,SEM-image contours are often extracted to serve such purposes.From contours,important information such as critical dimension and resist sidewall angle at any location can be estimated.Those geometrical information can be used for optical proximity correction(OPC)model verification and lithography hotspot detection,etc.Classical contour extraction algorithms based on local information have insufficient capability in dealing with noisy and low contrast images.To achieve reliable contours from noisy and low contrast images,information beyond local should be made use of as much as possible.In this regard,deep convolutional neural network(DCNN)has proven its great capability,as manifested in various computer vision tasks.Taking the full advantages of this maturing technology,we have designed a DCNN network and applied it to the task of extracting contours from noisy and low contrast SEM images.It turns out that the model is capable of separating the resist top and bottom contours reliably.In addition,the model does not generate false contours,it also can suppress the generation of broken contours when ambiguous area for contour extraction is small and non-detrimental.With advanced image alignment algorithm with sub-pixel accuracy,contours from different exposure fields of same process condition can be superposed to estimate process variation band,furthermore,stochastic effect induced edge placement variation statistics can easily be inferred from the extracted contours.

Extraction of line and rounded objects from underwater images

In the field of underwater image processing, the line and rounded objects, like mines and torpedoes, are the most common targets for recognition. Before further analysis, these two image patterns need to be detected and extracted from the underwater images in real-time. Using the subpixel position, direction and curvature information of an edge provided by Zernike Orthogonal Moment (ZOM) edge detection operators, an enhanced Randomized Hough Transform (RHT) to extract straight-lines is developed. This line extraction method consists of two steps: the rough parameters of a line are obtained robustly at first using RHT with large quantization in the Hough space and then the parameters are refined with line fitting techniques. Therefore both the robustness and high precision can be achieved simultaneously. Particularly, the problem of ellipse extraction is often computationally demanding using traditional Hough Transform, since an ellipse is characterized by five parameters. Based on the generalized K-RASAC algorithm, we develop a new ellipse extraction algorithm using the concept of quadratic curve cluster and random sampling technique. We first develop a new representation of quadratic curves, which facilitates quantization and voting for the parameter λ that represents a candidate ellipse among the quadratic curves. Then, after selecting two tangent points and calculating the quadratic parameter equation, we vote for the parameter λ to determine an ellipse. Thus the problem of ellipse extraction is reduced into finding the local minimum in the λ accumulator array. The methods presented have been applied successfully to the extraction of lines and ellipses from synthetic and real underwater images, serving as a basic computer vision module of the underwater objects recognition system. Compared to the standard RHT line extraction method and K-RANSAC ellipse extraction method, our methods have the attractive advantages of obtaining robustness and high precision simultaneously while preserving the merits of high computation speed and small storage requirement.