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Face sketches are being used in eyewitness testimonies for about a century. These sketches are crucial in finding suspects when no photo is available, but a mental image in the eyewitness's mind. However, research shows that current procedures used for eyewitness testimonies have two main problems. First, they can significantly disturb the memories of the eyewitness. Second, in many cases, these procedures...
This paper presented a video moving object segmentation and tracking system based on the active contour and the color classification models. First, the active contour model is applied to segment the target object in the initial frame. From the segmented object, the object and background regions are extracted. Then the object and the background regions are separately clustered according to color feature...
Exact segmentation of fingerprint image is very important for fingerprint singular points and minutiae features extraction. In this paper, a method for fingerprint image segmentation is proposed based on Support Vector Machine (SVM). The fingerprint image is broken into 16*16 prospects blocks and background blocks. The block average gray, block gray variance, block contrast and the largest peak of...
The influence of age progression on the performance of face verification systems is a challenging and largely open research problem. When only one reference and one test image per subject are available, in this paper we propose to manage the aging influence on the adult face verification system through a score-age stacking technique to find the global decision boundary which can change across the...
The use of region shape descriptors was investigated for categorisation of textile design images. Images were segmented using MRF pixel labelling and the shapes of regions obtained were described with generic Fourier descriptors. Each image was represented as a bag of shapes. A simple yet competitive classification scheme based on nearest neighbour class-based matching was used. Classification performance...
This paper describes a set of Performance Evaluation Tools (PETS) for document image zone segmentation and classification. The tools allow researchers and developers to evaluate, optimize and compare their algorithms by providing a variety of quantitative performance metrics. The evaluation of segmentation quality is based on the pixel-based overlaps between two sets of zones proposed by Randriamasy...
In this paper, a novel concept of segmental singular value decomposition (SegSVD) is proposed to represent a motion pattern with a hierarchical structure. The similarity measure based on the SegSVD representation is also proposed. SegSVD is capable of capturing the temporal information of the time series. It is effective in matching patterns in a time series in which the start and end points of the...
Human-area segmentation is a major issue in video surveillance. Many existing methods estimate individual human areas from the foreground area obtained by background subtraction, but the effects of camera movement can make it difficult to obtain a background image. We have achieved human-area segmentation requiring no background image by using chamfer matching to match the results of human detection...
We present a computer vision based approach for classifying graphical document images by matching distinct visual patterns present in them. To accomplish this task the image is first decomposed into congruous segments, some of which contain distinct patterns followed by image matching to identify the presence of a specific pattern in the image. We have used clustering based image segmentation to extract...
Based on remote sensing (RS), the updating method of land-use map is becoming one of the most important study direction in land use and cover change (LUCC) field over the world. This study have broken through traditional land use change detection methods based on two remote sensing images and matched the old land use vector data to the remote sensing image of new period, where making use of the vector...
Classification of coins is an important but laborious aspect of numismatics - the field that studies coins and currency. It is particularly challenging in the case of ancient coins. Due to the way they were manufactured, as well as wear from use and exposure to chemicals in the soil, the same ancient coin type can exhibit great variability in appearance. We demonstrate that geometry-free models of...
Given a set of algorithms, which one(s) should you apply to, i) compute optical flow, or ii) perform feature matching? Would looking at the sequence in question help you decide? It is unclear if even a person with intimate knowledge of all the different algorithms and access to the sequence itself could predict which one to apply. Our hypothesis is that the most suitable algorithm can be chosen for...
A UAV navigation system relying on GPS is vulnerable to signal failure, making a drift free backup system necessary. We introduce a vision based geo-referencing system that uses pre-existing maps to reduce the long term drift. The system classifies an image according to its environmental content and thereafter matches it to an environmentally classified map over the operational area. This map matching...
In this paper, we propose a novel Adaboost template to recognize human upper body poses from disparity images for natural human robot interaction (HRI). First, the upper body poses of standing persons are classified into seven categories of views. For each category, a mean template, variance template, and percentage template are generated. Then, the template region is divided into positive and negative...
The use of efficient classification methods is necessary for automatic fingerprint recognition systems. This paper introduces an approach to fingerprint classification by using Self-Organizing Maps (SOM). In order to be able to deal with fingerprint images having distorted regions, the SOM learning and classification algorithms are modified. The concept of `certainty' is introduced and used in the...
Color variation in medical images degrades the classification performance of computer aided diagnosis systems. Traditionally, color segmentation algorithms mitigate this variability and improve performance. However, consistent and robust segmentation remains an open research problem. In this study, we avoid the tenuous phase of color segmentation by adapting a bag-of-features approach using scale...
This paper proposes an universal method to detect and recognize road signs of any countries with any color or any of the existing shapes (e.g. circular, rectangular, triangular, pentagonal and octagonal). The presented system is invariant to transformation (e.g. translation, rotation, scale and occlusion). There are three main stages in the proposed algorithm: 1) segmentation based on the color features...
In this paper, a novel fusion method for gender classification from gait based on multi-view video sequences is proposed. At the feature level, each human silhouette in a whole gait period is segmented into eight different components. Then at the match score level, the discrimination distance of each corresponding component under every camera-view angle is respectively weighted. The two-dimension...
This paper describes developing of an occlusion robust tracking algorithm of pedestrians in the panning images by the combination between the S-T MRF model and pattern recognition methods of Snakes and HOG classifier. Tracking in panning images would extend the field of view of single camera. In addition, an algorithm to match pedestrians between cameras that have overlapping area with each other...
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