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Article
Selection, Detection, and Tracking of Video objects Based on FPGA

Authors: Zaki Y. Abid (BSc)1 --- Thamir R. Saeed2 --- Sameir A. Aziez3
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2015 Volume: 15 Issue: 1 Pages: 1-17
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Abstract – This paper presents a moving object tracker for monitoring system which can be used in a smart city. Kernel density estimation (KDE) algorithm has been used for representing a background model, while a minimum distance between the current image and the background has been used to extract the foreground. Also, morphological operations are carried out to remove the noise regions and to filter out ambiguous areas. The performance has been evaluated by determining the true, false, and miss detections of an object area. The optimal results have been obtained by adjusting the morphological operation sequence to be (close > thicken) combination by which the true-hits are 14 out of 16 while miss-number is 2 and zero false-hits, While, the percentage hit ratio was 87.5% (14 out of 16). Also, the salt noise introduction in video reduces the hit number from 14 to 11 when it increases from zero to 0.5 percent of the total frame pixels. The accepted absolute error ratio (in morphological properties of the matched object) is kept at 0.05 for all tests. The implementation has been built by using a combination of two platforms, ISE 14.6(2013) and Matlab(2013a) platforms, to avoid the size weakness of XC3S700A-FPGA board.


Article
Boundaries Object Detection for Skin Cancer Image using Gray-Level Co-Occurrence Matrix (GLCM) and features minutiae points

Author: Hind Rostom Mohamed
Journal: Journal of Al-Qadisiyah for Computer Science and Mathematics مجلة القادسية لعلوم الحاسوب والرياضيات ISSN: 20740204 / 25213504 Year: 2015 Volume: 7 Issue: 1 Pages: 160-172
Publisher: Al-Qadisiyah University جامعة القادسية

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Abstract

In the present paper, Boundaries Object Detection for Skin Cancer Image using Connected Components is proposed. We propose Connected Components algorithm which that capable of Segment with Extraction of connected boundaries for Skin Cancer Image Segmentation . The algorithm is proposed to create a color label image using the local features minutiae points in skin cancer as objects image . The performance of object Detection with Connected Components which are surround influence . The proposed scheme can serve as a low cost preprocessing step for high level tasks such shape based recognition and image retrieval. The experimental results confirm the effectiveness of the proposed algorithm.


Article
Object Tracking using Proposed Framework of KalmanGuided Harmony Search Filter
تتبع جسم باستخدام اطار مقترحلمرشح كالمان كموجه لمرشح الهارموني

Author: Akbas E. Ali* Dr. Alia K. Abdul Hassan* Dr. Hasanen S. Abdullah*
Journal: AL-yarmouk Journall مجلة كلية اليرموك الجامعة ISSN: 20752954 Year: 2015 Issue: 1 Pages: 120-137
Publisher: College Yarmouk University كلية اليرموك الجامعة

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Abstract

In this paper an improvementon the harmony filter is done by adding the Kalman filter after the improvisation process, toguide the filter to reach the convergence state at the lowest possible number of iterations, which means more ability for tracking the moving objects in real time performance, which is a crucial factor in the multi object tracking applications.

في هذا البحث تم تطوير فلتر البحث الهارموني وذلك باضافة فلتر كالمان اليه بعد عملية الارتجال لغرض توجيه فلتر الهارموني للوصول الى حالة التقارب باقل عدد ممكن من التكرارات،وهومايعني المزيدمن القدرةعلى تتبع الأجسام المتحركة في الأداءفي الوقت الحقيقي،والذي يعتبر عامل حاسم في تطبيقات تتبع الكائنات المتعددة


Article
Improving the Reliability of Object Recognition Based On Template Matching
تحسين موثوقية تميز الكائن بالاعتماد على المطابقة المتغيرة

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Abstract

Object recognition in computer vision is the task of finding a given object in an image or video sequence. During the last decades it has received increasing attention from the computer vision community for a variety of reasons, ranging from counting objects for industrial application to the development of practical biometric systems and interactive, emotion-aware and capable human–machine interfaces. There are variety of approaches for object recognition problem, depending on the type of object, the degree of freedom of the object and the target application. Template matching is the most advanced and intensively developed areas of computer vision and has been a classical approach to the problems of locating and recognizing of an object in the image. The object of this paper is to improve the reliability of object recognition by describing a modified method for template matching based on the Sum of Squared Differences (SSD) equation, that gives the highest margin between other template matching methods, the main advantage is that the high margin resulting from it can be considered as more safe to avoid wrongly detecting /recognizing an object.

تمييز الكائن في الرؤيا الحاسوبية يعني ايجاد كائن معلوم في صورة او تسلسل فيديو. خلال العقود الاخيرة يتلقى تمييز الكائن اهتماما متزايدا من رابطة الرؤيا الحاسوبية لعدة ضروريات, منها عد الكائنات في التطبيقات الصناعية لتطوير انظمة تدقيق حقيقية وتطوير تواصل تفاعلي, مدرك للانفعالات بين الانسان والالة. توجد عدة طرق لحل مشكلة تمييز الكائن اذ يعتمد ذلك على طبيعة الكائن ودرجة حريته والتطبيق المطلوب. تعتبر المطابقة المتغيرة من اكثر المجالات تقدما وتطورا في الرؤيا الحاسوبية ولاتزال طريقة تقليدية لحل مشاكل ايجاد وتمييز الكائن في الصور. يهدف هذا البحث الى تحسين موثوقية تمييز الكائن من خلال طريقة معدلة للمطابقة المتغيرة معتمدة على معادلة مجموع تربيع الفروقSSD)) ,والتي تعطي الهامش الاعظم مقارنة بالطرق الاخرى للمطابقة المتغيرة والذي يعتبر اكثر امانا لتجنب الايجاد والتمييز الخاطئ للكائن.

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