A pattern recognition system used for industrial inspection has to be highly reliable and fast. The reliability is essential for reducing the cost caused by incorrect decisions, while speed is necessary for real–time operation. In this paper we address the problem of inspecting optical media like Compact Disks and Digital Versatile Disks. Here, defective disks have to be identified during produ...

It is known that main drawbacks of the k-Nearest Neighbors classifier are related to the need for keeping all the training prototypes. Although there are several approaches capable to significantly reduce the size of the case base, they damage the classification accuracy. We propose a novel fuzzy approach that significantly reduces the prototypes base and also improves the classification accura...

This paper presents a method for features space optimization in a context of fuzzy image classification. Based on membership functions intersections, the method allows to select the most appropriate features for objects discrimination. Comparison of the eCognition nearest neighbor algorithms and fuzzy classification is provided with the use of un-optimized and optimized features sets.

E cient and accurate information retrieval is one of the main issues in multimedia databases. In content-based multimedia retrieval databases, contents or features of the database objects are used for retrieval. To retrieve similar database objects, we often perform a nearest-neighbor search. A nearest-neighbor search is used to retrieve similar database objects with features nearest to the que...

ÐWe consider a popular approach to multicategory classification tasks: a two-stage system based on a first (global) classifier with rejection followed by a (local) nearest-neighbor classifier. Patterns which are not rejected by the first classifier are classified according to its output. Rejected patterns are passed to the nearest-neighbor classifier together with the top-h ranking classes retu...

In this paper, a computer vision based system is introduced to automatically grade apple fruits. Segmentation of defected skin is done by three global thresholding techniques (Otsu, isodata and entropy). Stem−end/calyx regions falsely classified as defect are removed. Segmentations were visually best with isodata technique applied on 750nm filter image. Statistical features are extracted from t...

Classification of imbalanced datasets is one of the widely explored challenges of the decade. The imbalance occurs in many real world datasets due to uneven distribution of data into classes, i.e. one class has more instances while others have a few that results in the biased performances of traditional classifiers towards the majority class with large number of instances and ignorance of other...

In this article we present a novel approach to model visual comfort based on supervised statebased machine learning with Hidden Markov Models and one easy-to-obtain variable (illuminance measurements at the horizontal work-plane; Edesk). Data mining was performed on sensor data recorded for two years in a single-occupant office room and the developed model classifies workplane illuminances into...

To prevent blindness from diabetic retinopathy, periodic screening and early diagnosis are neccessary. Due to lack of expert ophthalmologists in rural area, automated early exudate (one of visible sign of diabetic retinopathy) detection could help to reduce the number of blindness in diabetic patients. Traditional automatic exudate detection methods are based on specific parameter configuration...

The realization that entanglement can affect macroscopic properties of bulk solid-state systems is a challenge in physics and Chemistry. Theoretical physicists often are considered the entanglement between nearest-neighbor (NN) spins and tried to find its characterizations in terms of macroscopic thermodynamics observables as magnetization and specific heat. Here, we focus on the entanglement b...