This paper studies bruise detection in apples using 3-D imaging. Bruise detection based on 3-D imaging overcomes many limitations of bruise detection based on 2-D imaging, such as low accuracy, sensitive to light condition, and so on. In this paper, apple bruise detection is divided into two parts: feature extraction and classification. For feature extraction, we use a framework that can directly extract local binary patterns from mesh data. For classification, we studies support vector machine. Bruise detection using 3-D imaging is compared with bruise detection using 2-D imaging. 10-fold cross validation is used to evaluate the performance of the two systems. Experimental results show that bruise detection using 3-D imaging can achieve better classification accuracy than bruise detection based on 2-D imaging.
This paper proposes an algorithm for book segmentation based on bookshelves images. The algorithm can be separated into three parts. The first part is pre-processing, aiming at eliminating or decreasing the effect of image noise and illumination conditions. The second part is near-horizontal line detection based on Canny edge detector, and separating a bookshelves image into multiple sub-images so that each sub-image contains an individual shelf. The last part is book segmentation. In each shelf image, near-vertical line is detected, and obtained lines are used for book segmentation. The proposed algorithm was tested with the bookshelf images taken from OPIE library in MTU, and the experimental results demonstrate good performance.
We propose a cluster-driven trilateral filter for speckle reduction in ultrasound images. In addition to operating in the spatial dimension and the intensity dimension, the proposed filter also merges clustering information simultaneously. We compare the proposed filter with a normalized bilateral filter for speckle reduction using real 3-D ultrasound images. Our experimental results indicate that the cluster-driven trilateral filter exhibits better performance for speckle reduction and edge feature preservation than the normalized bilateral filter. In addition, we investigate the graphic processing unit (GPU) technique and apply it to the proposed 3-D filter. We design and test a GPU framework and compare it with a single-core CPU framework. Our experimental results show that the GPU-accelerated trilateral filter can obtain a roughly 20-fold increase in speed.