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Visual reranking has become a widely-accepted method to improve traditional text-based image search results. The main principle is to exploit the visual aggregation property of relevant images among top results so as to boost ranking scores of relevant images, by explicitly or implicitly detecting the confident relevant images, and propagating ranking scores among visually similar images. However,...
Gap Completion is a key step in the process of linking of edges into contours towards generating meaningful boundaries. The likelihood of completing a gap between two edges has been approached either indirectly through studying optimal completion contours such as Elastica and Euler Spiral, or through the statistics of co-occurrence. These studies do not address the issue of finding appropriate candidates...
Many cues have been proposed for contour detection or image segmentation. These include low-level image gradients to high-level information such as the identity of the objects in the scene or 3D depth understanding. While state-of-the-art approaches have been incorporating more cues, the relative importance of the cues is unclear. In this paper, we examine the relative importance of low-, mid- and...
Depth ordering is instrumental for understanding the 3D geometry of an image. Humans are surprisingly good at depth ordering even with abstract 2D line drawings. In this paper we propose a learning-based framework for depth ordering inference. Boundary and junction characteristics are important clues for this task, and we have developed new features based on these attributes. Although each feature...
Curve fragments, as opposed to unorganized edge elements, are of interest and use in a large number of applications such as multiview reconstructions, tracking, motion-based segmentation, and object recognition. A large number of contour grouping algorithms have been developed, but progress in this area has been hampered by the fact that current evaluation methodologies are mainly edge-based, thus...
The Agricultural industry on the whole is ancient so far. Quality assessment of grains is a very big challenge since time immemorial. The paper presents a solution for quality evaluation and grading of Rice industry using computer vision and image processing. In this paper basic problem of rice industry for quality assessment is defined which is traditionally done manually by human inspector. Machine...
Web security has become a critical and challenging issue due to the growth of Internet. BOT is one of the most malicious threats to the web services. It runs automated tasks over the internet and creates problem. One solution for securing web from BOT is to develop CAPTCHA. CAPTCHA is acronym for Completely Automated Public Turing test to tell Computers and Humans Apart. CAPTCHA may be textual or...
The main purpose of this paper is to make table tennis robots complete the hit table tennis ball action by imitating human's behavior. The main strategy is to record a video of action which people played the table tennis, then analysis the video of the racket trajectory. The racket in the image is extracted by image processing when the each frame is captured in the video. Then three-dimensional coordinates...
During the wafer dicing process, the die are separated from a wafer of semiconductor. The dicing saw will leave the damage on the backside of the wafer and this damage needs to be accessed and inspected. The main damage on the backside of the wafer is chipping and delamination that can reduce the die strength. Backside chipping becomes a yield issue when micro-cracks exceed a certain length which...
We propose a fully automatic method to segment the dentate nucleus using diffusion weighted images (DWI). Initialization of the dentate nucleus is produced by combining the information from tractography results on the diffusion tensor images (reconstructed from DWI) and b0 images. A geometric de-formable model (GDM) with generalized gradient vector flow (GGVF) is then applied on the b0 image to generate...
Many methods on extracting 3D information from 2D images have been studied since 1990s, especially the depth information extraction. A novel approach for depth extraction is proposed and implemented in this paper. About 30 images are taken especially for this case study and experiments are conducted on the Stanford Range Image Data. Results show that this approach is generally suitable for most of...
This paper presents a new generic framework for human visual system inspired object detection and recognition and introduces the idea of feature extraction based on the human visual sensitivity. These methods can greatly enhance robotic vision applications. Additionally a new computationally effective object detection algorithm is presented based on image morphology and visual sensitivity. This new...
Face recognition, as one of the most interesting and successful applications of image understanding and machine vision, has grown a lot of attention during the past years. Basically human faces are very similar in structure with minor differences from person to person. In this paper a new robust face recognition method is proposed which exploit edge-based features of faces. The performance of this...
In this paper, we propose a system to obtain a depth ordered segmentation of a single image based on low level cues. The algorithm first constructs a hierarchical, region-based image representation of the image using a Binary Partition Tree (BPT). During the building process, T-junction depth cues are detected, along with high convex boundaries. When the BPT is built, a suitable segmentation is found...
The new breakthrough in technology has opened new chances for researchers to develop more advance video surveillance system to provide human a more liveable city. Hand detection from silhouette for video surveillance application is important as it enables the tracking of human hand across video frames. This paper describes the algorithm for hand detection from human silhouette for video surveillance...
Biometrics systems based on ear are still in need of more investigation to make it robust and accurate. The most critical step in ear recognition is segmentation as all subsequent steps will depend on the accuracy of segmentation. In this paper, a robust ear segmentation method is suggested. The proposed method consists of a sequence of steps. First, a Biased Normalized Cuts method is applied to initiate...
The ever-growing availability of multimedia data creates a strong requirement for efficient tools to manipulate and present data in an effective manner. The contributions of this paper consist of collation of audio and video parameters on system test level that allows for the analysis of test results. A key issue in automated summary construction is the evaluation of quality of audio and video with...
A new block-based multi-metric fusion (BMMF) approach is proposed for perceptual image quality assessment. The proposed BMMF scheme automatically detects image content and distortion types in a block via machine learning, which is motivated by the observation that the performance of an image quality metric is highly influenced by these factors. Locally, image block content is classified into three...
Normalised cuts algorithm requires massive similarity measurement computation for image segmentation. Since a digital camera at present has the capability to produce high resolution image, it will be inevitably that resizing image into suitable resolution at which the algorithm can perform image segmentation with minimal burden. While retaining the important features in the images, natural images...
The block-based multi-metric fusion (BMMF) is one of the state-of-the-art perceptual image quality assessment (IQA) schemes. With this scheme, image quality is analyzed in a block-by-block fashion according to the block content type (i.e. smooth, edge and texture blocks) and the distortion type. Then, a suitable IQA metric is adopted to evaluate the quality of each block. Various fusion strategies...
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