توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Cellular Learning Automata–Based Color Image Segmentation using Adaptive Chains
نویسنده(ها): ، ،
اطلاعات انتشار: چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۶
This paper presents a new segmentation method for color images. It relies on soft and hard segmentation processes. In the soft segmentation process, a cellular learning automata analyzes the input image and closes together the pixels that are enclosed in each region to generate a soft segmented image. Adjacency and texture information are encountered in the soft segmentation stage. Soft segmented image is then fed to the hard segmentation process to generate the final segmentation result. As the proposed method is based on CLA it can adapt to its environment after some iterations. This adaptive behavior leads to a semi content–based segmentation process that performs well even in presence of noise. Experimental results show the effectiveness of the proposed segmentation method<\div>

۲Real–Time Multiple Face Detection and Tracking
نویسنده(ها): ، ،
اطلاعات انتشار: چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۶
In recent years, processing the images that contain human faces has been a growing research interest because of establishment and development of automatic methods especially in security applications, compression, and perceptual user interface. In this paper, a new method has been proposed for multiple face detection and tracking in video frames. The proposed method uses skin color, edge and shape information, face detection, and dynamic movement analysis of faces for more accurate real–time multiple face detection and tracking purposes. One of the main advantages of the proposed method is its robustness against usual challenges in face tracking such as scaling, rotation, scene changes, fast movements, and partial occlusions.<\div>
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