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Abstract-In recent years, occurrence rates of skin melanoma have shown a rapid increase, resulting in enhancements to death rates. Based on the difficulty and subjectivity of human clarification, computer examination of dermoscopy images has thus developed into a significant research field in this area. One the reasons for applying heuristic methods is that good solutions can be developed with only reasonable computational exertion. This paper thus presents an artificial swarm intelligence method with variations and suggestions. The proposed artificial bee colony (ABC) is a more suitable algorithm in comparison to other algorithms for detecting melanoma in the skin tumour lesions, being flexible, fast, and simple, and requiring fewer adjustments. These is characteristics are recognized assisting dermatologists to detect malignant melanoma (MM) at the lowest time and effort cost. Automatic classification of skin cancers by using segmenting the lesion’s regions and selecting of the ABC technique for the values of the characteristic principles allows. Information to be fed into several well- known algorithms to obtain skin cancer categorization: in terms of whether the lesion is suspicious, malignant, benign (healthy and unhealthy nevi). This segmentation approach can further be utilized to develop handling and preventive approaches, thus decreasing the danger of skin cancer lesions. One of the most significant stages in dermoscopy image examination is the segmentation of the melanoma. Here, various PH2 dataset image were utilized along with their masks to estimate the accuracy, sensitivity, and specificity of various segmentation techniques. The results show that a modified automatic based on ABC images have the highest accuracy and specificity compares with the other algorithms. The results show that a modified automatic based on ABC images displayed the highest accuracy and specificity in such testing.

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ABSTRACT In this aera of smart applications, multi-camera tracking technique has established itself as an emerging technology that is being popular day by day. Addition identification of the active speaker using camera assisted microphone array. The possibility of identifying the active speaker component and the camera automatically turns towards the sound source. The PZT cameras work not limited to the human voice, but it is sensitive to all the vibration of sound and works on the camera and audio recording is not observed, but it can record video conference. It has been programmed to save the information about the speaker or the sound source and the ability of displaying it at the anther time if the need arises. According to the option of night vision by adding an infrared sensor. This type of sound sensitive surveillance cameras is of a great important and urgent need, because of its benefit commensurate with all requirement. The camera tracking has developed pervious research on surveillance cameras, with an external cover suitable for environmental changes, and a few very high efficiencies. Assessment by user and independent codes suggests promising initial results and future work. We associate the projected 3D tracker against anther procedures on the all database and on an anew collected data group with sensors, which we variety presented to the investigation public. A speaker position combined with camera image protects effective and accurate tracking structure. The scheme was applied Arduino microcontroller for image processing and development of tracking system and increasing the accuracy of the tracking of living organisms.