Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> From a structural point of view, a textured image is considered to be composed of skeleton and background primitives which occur repeatedly according to certain placement rule. Identification of defects in textured images is an important topic in computer vision. In this paper, an approach to defect detection is developed. A textured image is first thresholded using histogram analysis. Then it is mapped into a special data structure called the skeleton representation. Based on both location and length histograms from the data structure, several statistical measurements are defined. These measurements are used to identify and locate defects such as fluctuation, mean jump, and end influency in the textured image. The experimental results show satisfactory performance of this approach and its potential usefulness in industrial environments. <s> BIB001 </s> Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> This paper provides a synthesis of a number of textile flaw detection techniques. The review highlights the issues pertaining to textile visual quality inspection and outlines its objectives and problems. Furthermore it looks at the general taxonomy of texture analysis approaches and their suitability for the task of textile quality inspection. The paper also details and provides a comparison of some of our most recent solutions to this problem and addresses the issues of their specifications for the real-time implementation. <s> BIB002 </s> Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> Morphological operations such as erosion and opening are applied to both direct and spatially filtered images of test fabrics to identify defects. Detecting defects morpholog ically on spatially filtered images of fabrics produces better results, particularly when the fabric is fine and contains defects of small size. The diffraction pattern of the test fabric is obtained optically by illuminating it with a collimated laser beam. A spatial filter is placed at the Fourier plane to remove the periodic grating structure of the fabric from the image. Morphological operations with a critically selected structuring element are then applied to the image after suitable pre-processing. <s> BIB003 </s> Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> In a PCM modem system in which equivalence classes are used to communicate information from a transmitter to a receiver, a method is provided to solve the problem of 180° phase reversals in the communications channel which result in a garbled transmission. This is accomplished by remapping the equivalence classes into a form that can be differentially encoded and decoded such that equivalence class identity is not lost during a phase reversal of the channel. <s> BIB004 </s> Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> Manufacturing defects in flat surface products such as thin films, paper, foils, aluminum plates, steel slabs, fabrics, and glass sheets result in degradation of the visual quality of the product image. This leads to less satisfied customers, waste of material, and bad company reputation. This research presents a novel application of image visual quality measures such as the multiscale structural similarity index (MS-SSIM). A novel algorithm has been implemented for fast detection and location of defects in many flat surface products. Comparison of the proposed algorithm with the state-of-the-art approaches indicate promising results. A defect detection accuracy of 99.1 % has been achieved with 98.62 % precision, 97.7 % recall/sensitivity, and 100 % specificity. The discriminant power shows how well the MS-SSIM discriminates very effectively between normal and abnormal surfaces. The MS-SSIM has resulted in much better performance than the single-scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented approach are as follows: scale invariance, avoiding the problem of parameter selection in the case of the state-of-the-art Gabor filter banks based approach, the higher detection accuracy, and the quasi real-time processing speed. <s> BIB005 </s> Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> This paper proposes an unsupervised model to inspect various detects in fabric images with diverse textures. A fabric image with defects is usually composed of a relatively consistent background texture and some sparse defects, which can be represented as a low-rank matrix plus a sparse matrix in a certain feature space. The process is formulated as a least squares regression based subspace segmentation model, which is convex, smooth and can be solved efficiently. A simple and effective prior is also learnt from local texture features of the image itself. Instead of considering only the feature space' s global structure, the local prior is incorporated with it seamlessly by the proposed subspace segmentation model to guide and improve the segmentation. Experiments on a variety of fabric images demonstrate the effectiveness and robustness of the proposed method. Compared with existing methods, our method is more robust and locates various defects more precisely. <s> BIB006 </s> Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY <s> Structural Approaches <s> A technology to stabilize the process by inspecting fine cracks in advance before mass and fatal defects occur is important. We propose a vision inspection system for the edge cracks of cold-rolled steel strips. It is important to detect the edge cracks of cold-rolled steel sheets early because they can result in plate breakage. There are two major components to achieve a suitable defect inspection system. The first is an optical system design technique that generates an image that can easily distinguish a defect area from a nondefect area. The second is an automatic detection algorithm technique that can accurately detect the position and shape of a defect in an image generated from an optical system. The optical part is designed using a backlight technique, which places the camera on the top of the strip and irradiates light from the bottom to the top. The defect detection algorithm detects the defects based on morphological operations. It is important to design the structuring elements that determine the performance of the detection algorithm. We optimized the structuring elements using the exhaustive dynamic encoding algorithm for searches. Experiments were conducted on the obtained images by installing the proposed system in actual production lines. The experimental results show the effectiveness of the proposed system. <s> BIB007
Structural Approaches (SA) mostly focus on the spatial location of the texture elements. These elements can be extracted from the texture and described as texture primitives. Applying spatial arrangement rules to texture primitives can result in a dynamic texture model. The texture primitives are mostly simple grey-scale regions, line segments or individual pixels. These elements are always used in a combination with placement rules which are derived from the geometric relationships or spatial statistics of these primitives. After revising several publications about SAs (see Table 2 ), it is possible to state that this approach performs much better on patterned regular textures. Several methods for SAs have been developed, such as the one proposed by Chen and Jain BIB001 that describes a model with a skeleton structure of the texture or the one proposed by Bennamoun and Bodnarova BIB002 that describes an approach called texture blob detection: both approaches are made for defect detection on fabric images. Wen and Xia  examined the surface of leather extracting the edge segments and statistically evaluated them based on their physical attributes. Morphological operators are other SAs, developed by Matheron and Serra BIB004 in 1964. They give an outstanding opportunity for segmenting defects and general defects detection, as reported in BIB003 . Recently, Tolba and Raafat BIB005 proposed a multiscale structural similarity index (MS-SSIM)-based method, which discriminated abnormal features with a 99.1% success rate. Yun, Jong Pil et al. BIB007 proposed an automatic defect detection optical system based on morphological operations, using backlight technique. Finally, in BIB006 , the authors developed a new method: the prior knowledge guided least squares regression (PG-LSR) and solved the subspace segmentation problem. However, no detailed results of the detection were reported.