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We propose a simple yet effective pre-classification method for background removal and bruise separation for automatic fruit sorting and grading systems. Different fruits require different pre-classification segmentation approach driven by a unique logic in regard of specific appearance of the concerning fruit. The proposed method is experimented upon guava samples having different tones of bruises,...
Traffic sign recognition is an important step for integrating smart vehicles into existing road transportation systems. In this paper, an NVIDIA Jetson TX1-based traffic sign recognition system is introduced for driver assistance applications. The system incorporates two major operations, traffic sign detection and recognition. Image color and shape based detection is used to locate potential signs...
A comprehensive Arabic handwritten text database is an important resource for Arabic handwritten text recognition research. It is essential for training text recognition algorithms and vital for evaluating the performance of these algorithms. In this paper, we present a database that includes manuscripts from the Islamic heritage project (IHP), consisting of 333 historical manuscripts written by 302...
The Cognitive learning process of a human being normally begins with sensory inputs. This process of learning gets hampered in case of persons with one or more perceptual disability. Vision being one of the most important perception, maximum learning happens through it. The absence of vision in humans is often supported by Tactile or Auditory perception during the cognitive learning process. Colour...
In this paper we proposed SVM algorithm for MNIST dataset with fringe and its complementary version, inverse fringe as feature for SVM. MNIST data-set is consists of 60000 examples of training set and 10000 examples of test set. In our experiments we started with using fringe distance map as feature and found that the accuracy of system on trained data is 99.99% and on test data it is 97.14%, using...
This paper presents a simple color recognition algorithm using digital image processing techniques and pattern recognition to eliminate the subjectiveness of manual inspection of the quality of coconut sugar based on Philippine National Standard. The image processing was built using MATLAB functions through RGB acquisition. The Backpropagation Artificial Neural Network was used in this project to...
This paper presents a new algorithm for colorizing gray scale natural still images. The algorithm uses artificial neural network (ANN) to predict the low frequency discrete cosine transform (DCT) components of the RGB channels. A set of natural color images are used to train three ANNs. The trained networks estimates the RGB layers of the gray scale image that best match a set of training colored...
Machine vision is still a challenging topic and attracts researchers to carry out researches in this field. Efforts have been placed to design machine vision systems (MVS) that are inspired by human vision system (HVS). Attention is one of the important properties of HVS, with which the human can focus only on part of the scene at a time; regions with more abrupt features attract human attention more...
Many attempts have been made to identify the region of interest in an image. In this paper, we have provided a new approach for ROI detection using the output of image annotation. Our claim is that because ROI is a subjective concept, a method should be used to diagnosis human mental models and for this purpose, we have used KNN base annotation in our method. Because many people in pictures that are...
Tree models for human pose estimation have been prevailed in the last decade, which are effective in human pose estimation. This paper aims to incorporate the appearance symmetry of human limb parts into tree model and address the problem of the wrong detection of human limbs. For a pair of symmetrical limbs, such as for legs and arms, their appearances are similar that can use a distance to represent...
Every student arrives with full digital competency from secondary school to higher education. Is it a true statement? Teachers and professors in higher education expect that according to the National Curricula, students start to learn ICT - info-communication technology - in primary school and improve them in secondary education. It would be a theoretical situation but the reality is totally different...
Person re-identification is an important problem in visual surveillance where appearance plays a key role. Color is one of the widely used appearance features and utilizing more color spaces doesn't imply benefit of performance enhancement. That's because the poor performance color spaces influence on the high ones. So it is significant to evaluate the performance of different color spaces for person...
All manufacturing companies have been trying to integrate intelligence-oriented strategies into their workflow. This saves time and money and leads to a better quality of goods. This intelligent strategy is in the subject area of Artificial Intelligence (AI). In our contribution a “Knowledge-Based System” (KBS) for image processing and pattern recognition, machine learning (ML) is used to measure...
This paper presents a low-level color descriptor which describes the color distribution of a color image as a weighted subspace in the color space, namely eigenvectors and eigenvalues of the distribution. Thanks to low-dimensionality of color space, the proposed descriptor can provide compact description and fast computation. Furthermore, specialized for color distribution matching, it is more efficient...
This study presents a hybrid hand tracking system using Pixel-Based Hierarchical-Feature AdaBoosting (PBHFA), skin color segmentation, and codebook background cancellation. The object of this approach is to construct a system which is able to cope with hand detection and further tracking tasks. To reduce the effect of false positive, the skin color segmentation and the foreground subtraction by applying...
This paper addresses the problem of object tracking by learning a discriminative classifier to separate the object from its background. The online-learned classifier is used to adaptively model object's appearance and its background. To solve the typical problem of erroneous training examples generated during tracking, an online multiple instance learning (MIL) algorithm is used by allowing false...
“Gain-Based Separation” is a novel heuristic that modifies the standard multiclass decision tree learning algorithm to produce forests that can describe an example or object with multiple classifications. When the information gain at a node would be higher if all examples of a particular classification were removed, those examples are reserved for another tree. In this way, the algorithm performs...
A great deal of region-related concept detection algorithms have been proposed so far, but there are few of them concerning about the problem of mismatched regions at training and testing stages. In order to investigate the mismatch problem in region-related concept detection, we introduce three kinds of methods to annotate the datasets, and then conduct experiments on differently annotated training...
A new framework for high-level feature extraction (or semantic concept detection) is proposed. In this system, features at different granularities are extracted, and four classifiers with complementary features for each concept are employed, and then the results are fused. We have evaluated 18 fusion schemes, and choose the best one for each concept to form the final results. The experiments on the...
In this paper, we propose a method to reduce the false alarm rate or alternatively to improve the detection rate of a local detector for individuals within dense crowds. The detected windows from a Viola-type head detector are processed in a second pass by a cascade of boosted classifiers working with Haar-like features to improve performance. The latter classifier uses color bin images, constructed...
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